Data Matrix Of Cpi Data Distribution After Transformation...

Data Matrix Of Cpi Data Distribution After Transformation...
After Data Transformation Figure 5.21. Histogram Plot of CPI Data Distribution after
Transformation Figure 5.22. Normal Q–Q Plot of CPI Data Distribution after Transformation Figure
5.23. Histogram Plot of SPI Data Distribution after Transformation Figure 5.24. Normal Q–Q Plot
of SPI Data Distribution after Transformation
After executing two–step method of data transformation (Templeton, 2011), the researcher attained
probable means and medians for both CPI (1.00) and SPI (1.05). Likewise, the Skewness figures
comply with logically normalizing rules, in which the plausible range of normal and near–normal
distribution is from –1 to 1. Conforming to histogram and normal Q–Q plots above, the researcher
successfully reconstructed CPI and SPI data and prepared for the further inferential statistics
examination. Descriptive statistics for CPI and SPI after transforming to normal and near–normal
distribution are as in Table 5.7.
Table 5.7
Descriptive Statistics of Adjusted Dependent Variables (CPI & SPI) Statistic Std. Error
ADJ CPI Mean 1.00 .013 95% Confidence Interval for Mean Lower Bound .97 Upper Bound 1.03
5% Trimmed Mean 1.00 Median 1.00 Variance .013 Std. Deviation .115 Minimum 1 Maximum 1
Skewness .030 .276 Kurtosis –.214 .545
ADJ SPI Mean 1.05 .009 95% Confidence Interval for Mean Lower Bound 1.03 Upper Bound 1.07
5% Trimmed Mean 1.05 Median 1.05 Variance .006 Std. Deviation .079 Minimum 1 Maximum 1
... Get more on HelpWriting.net ...

Data And Methodology Of M & A
3. Data and Methodology This section begins with a description of the process in constructing the
sample used for the study. To obtain the sample of M&A deals, data was primarily sourced from the
Thomson Reuters Securities Data Company (SDC) Platinum Database, a widely used database for
M&A studies (Harford, 2005; Popli and Sinha, 2014; Carow et al, 2004). To obtain financial
information such as company daily share prices and index level data, the DataStream database was
utilized. The section then covers the quantitative methods used to test the hypotheses regarding the
performances of first movers and late followers in an M&A wave. 3.1. Sample 3.1.1. Broad Sample
An initial sample of 33, 434 completed M&A deals for the period 1990–2014 by publicly listed
acquiring firms with deal value above USD$10 million (m) was extracted from Thomson Reuters
SDC Platinum Database. 3.1.2. Wave Identification Based on the broad sample, distinct wave
periods were identified. A simple wave identification method was employed based on common
characteristics associated with M&A waves. M&A waves are described as periods beginning with
low M&A activity, which sharply increases before reaching a peak level, followed by a fall in M&A
activity (Popli and Sinha, 2014; Hou et al, 2015; Haleblian et al, 2012). The broad sample was
organized in terms of the total number of deals announced on a yearly basis from 1990–2014 as seen
in Graph 1a. A trend line was imposed which illustrated two wave

What Are The Independent Variables?
1. What are the independent variables in this study? What are the dependent variables?
ANSWER: The independent variables in this study is treatment & gender. The dependent variables
in this study are worry & emotion.
2. Why is a factorial MANOVA appropriate to use for this research design?
ANSWER: A factorial MANOVA is appropriate to use for this research design because there is more
than one independent variable, each independent variable is discrete variables. The study has more
than one dependent variable and each dependent variable is measured on a continuous scale.
3. Did you find any errors that the researcher made when setting up the SPSS data file (don 't forget
to check the variable view)? If so, what did you find? How did you correct it?
ANSWER: Yes, there were coding errors made with measures. The independent variables treatment
and gender need to be switched to nominal. The dependent variables worry and emotion should be
scale.
4. Perform Initial Data Screening. What did you find regarding missing values, univariate outliers,
multivariate outliers, normality?
ANSWER: There were no missing values within the dependent variables. The skewness and
kurtosis are less than 1.0 on both of the dependent variables and the Shapiro–Wilks' test: p value for
both dependent variables are larger than .001. There is one outlier for the independent variable
worry, but this needs to be inspected to decide if it is an error of coding, a possible example of a true
value found in

Impact Of Political Connections On Performance And...
Overview: This paper investigates the impact of political connections on performance and financing
decisions of public listed companies. There is a large body of literature documenting the impacts of
political connections on the firms; however most of the studies are focused on a single country; for
example Fisman (2001), Mobarak and Purbasari (2006) on Indonesia, Johnson and Mitton (2003) on
Malaysia, Agrawal and Knoeber (2001) on US and Sapienza (2004) on Italy. Faccio (2006) and
Faccio, Masulis and McConnell (2006) however, used an international sample and a cross country
analysis approach to investigate the phenomenon of political connectivity across the globe. In this
paper, the authors identify the gap in the literature to argue the ... Show more content on
Helpwriting.net ...
Hypothesis 2: After the connection is established, politically connected firms become more indebted
than their non–connected peers. Hypothesis 3: After the connection is established, politically
connected firms use more long–term debt than non–connected peers. Results show a statistically
significant increase in performance after a firm establishes a political connection. The results also
compare financial leverage, use of long term debt and liquidity ratio three years before and after the
establishment of political connection to report an increase in all these three measures of financing
decisions, thus accepting all three hypotheses. Outline of research method and data analysis: This
research uses the definition of Faccio (2006) to identify politically connected firms. A firm is
defined as politically connected if any one of its officers (Director, CEO, Chairman, Vice chairman
or Secretary) or a large shareholder (holding at least 10% voting rights) is a politician (member of
parliament or cabinet, prime minister or president) or is closely related to a politician or political
party. The research updates and extends the Faccio (2006) databases of company officers and
politicians, and uses procedures and resources similar to those of Faccio (2006) to identify
politically connected firms. The authors then move a step ahead by identifying the date of
establishment of political connection i.e the date when a politician was appointed a board member or
when a company

Statistical Assumptions Of Substantive Analyses Across The...
Nimon, K. (2012). Statistical Assumptions of Substantive Analyses Across the General Linear
Model: A Mini–Review. Frontiers in Psychology Front. Psychology, 3(322).
When using inferential statistics depends on the sampling technique used as well as the
characteristics of the population data. This dependency does assume that the sample and population
meet certain criteria. The criteria is called statistical assumptions, and if there are violations of these
statistical assumptions that are not addressed, than the data may not be interpreted correctly. In
particular, Type I or Type II errors may be increased or decreased incorrectly. Nimon's (2012) article
focused on assumptions associated with substantive statistical analyses across the ... Show more
content on Helpwriting.net ...
Using unreliable data may cause underestimation which increase the probability of Type II errors. If
there is correlated error, we may see unreliable data to be overestimated which would increase the
risk of Type I errors. To satisfy the assumption of error–free data, researchers may conduct and
report analyses using latent variables as opposed to observed variables. This technique is called
structural equation modeling (SEM). This is where latent variables are formed from item scores, the
former of which becomes the unit analyzed. It is important to note that SEM is a large sample
technique. A researcher can also delete a few items to raise the reliability of an observed score, but
this should be reported along with the accompanied estimated of the reliability with and without the
deleted items. Some researchers consider measurement to be an assumption while others do not.
Nimon (2012) does state because measurement levels play such a pivotal role in statistical analyses
decision trees, it would not be recommended to lower the measurement level of data unless certain
characteristics are met. This may discard important information and may produce misleading or
erroneous information. Yet another assumption, is the assumption that inferential statistics in
psychological and educational research produce population data that is normally distributed. This
does depend on the analysis conducted, such as univariate, multivariate,

Analysis Of The Article ' Volunteerism Among Homeless...
The article, "Volunteerism among Homeless Persons with Developmental Disabilities," by Larry G.
Morton II and Giovanina Gardiner conducted the study in at George Warren Brown School of Social
Work, Washington University in St. Louis, Missouri. The researchers discuss about the adults
hardships and struggles these individuals are exposed to on a daily basis. In addition, this vulnerable
population is excluded from mainstream society. The authors that conducted this study did a
comparison on homeless individuals who were diagnosis with a developmental delay to determine if
there is a correlation between volunteerism and community integration. Furthermore, the intent of
this article is "to take Bowgett's study a step further by reporting the level of volunteerism in an
urban sample of homeless persons with developmental disabilities. The research question is does
volunteerism suggest healthy community integration among this ample of homeless persons with
developmental disabilities?" ( (Gardiner, Morton, & Cunningham–Williams, 2010, p. 2). In fact, the
demographics of this article were citizens residing in two suburban St. Louis city public parks. Also,
the following stipulation include: being age eighteen or older, having received special education
services for development disability during their educational career, and being currently homeless (
i.e. staying outdoors, in a shelter, temporarily doubled up in another's residence, or staying in a place
not meant for human

Unilateral Amputees: A Case Study
20.5% of the subjects experienced one or more falls during their rehabilitation and the difference
between bilateral and unilateral amputees was not mentioned. These incidences represent, as do the
surgical patients, a group which is at a particularly high risk of falling. However, it can be shown
that the falling incidence is higher in the amputee inpatient rehabilitation population than the
reported incidence in that of the surgical ward. This deviation can be explained by the fact that the
postoperative amputees are less mobile than their rehabilitation counterparts because of their need to
recover from the surgery [12]. So, in order to compare between the two incidences, the distinguished
mobility of the two different populations should

Hypervigilance
Citation Kimble, M. O., Fleming, K., & Bennion, K. A. (2013). Contributors to hypervigilance in a
military and civilian sample. Journal of Interpersonal Violence, 28(8), 1672–1692. doi:
10.1177/0886260512468319 Introduction A nonexperimental research study was conducted to
explain and predict hypervigilance in the returning soldier. Specifically, the researchers aimed to
determine if military training is associated with hypervigilance, if trauma alone can produce higher
levels of hypervigilance, if soldier deployment is associated with hypervigilance, and if disorders
(depression, dissociation, and PTSD) predict hypervigilance above and beyond trauma and
deployment. Sample Non–random purposive sampling and convenience sampling techniques ...
Show more content on Helpwriting.net ...
A Pearson's correlation coefficient was computed and indicated the older a person is, the more likely
they are to experience hypervigilance. To determine if military training was associated with
hypervigilance, a univariate ANCOVA was conducted comparing military cadet undergraduates to
non–military undergraduates. Results indicated that military cadets were no more hypervigilant than
the non–military undergraduates. To determine if trauma alone produced higher levels of
hypervigilance, a univariate ANOVA was conducted using the entire sample, and trauma was found
to be a significant predictor of hypervigilance only when PSS was removed as a covariate. Finally, a
hierarchical multiple regression using only traumatized participants in the study was conducted to
determine if deployment was associated with hypervigilance, and if disorders (depression,
dissociation, and PTSD) predicted hypervigilance above and beyond trauma and deployment.
Findings indicated veterans with PTSD have the highest hypervigilance scores. A follow–up t–test
indicated that the community members with PTSD did not differ significantly from the deployed
soldiers without PTSD with

Multivariate Analysis Of Variance And Multivariate Analysis
MULTIVARIATE ANALYSIS OF VARIANCE (MANOVA) Multivariate analysis of variance
(MANOVA) is a statistical analysis used when a researcher wants to examine the effects of one or
more independent variables on multiple dependent variables. This method is an extension of the
analysis of variance (ANOVA) model and is the most commonly used multivariate analysis in the
social sciences. MANOVA tests whether there are statistically significant, or not due to chance,
mean differences among levels of the independent variable(s) on a linear combination of dependent
variables. Multivariate analysis of variance tests belong to a larger family of statistical techniques
known as the General Linear Model, which include analyses such as ANOVA, multiple types of
regression, and repeated measures designs. MANOVA is an inferential statistical analysis, meaning
that the communication researcher deduces a causal relationship between the independent
variable(s) and the dependent variables and can then take the results of their study conducted on a
smaller sample, or subset of the population, and generalize those results to a larger population. A
researcher uses MANOVA to answer questions about how the combination of multiple dependent
variables differs with respect to the chosen independent variable(s). The researcher is hoping to see
a stable pattern of cause and effect between the independent and dependent variables (DV). To
briefly review, independent variables (IV) refer to those variables that

Bankruptcy: Vodafone and Samsung
Table of Contents Executive Summary 2 Background Information 2 Vodafone 2 Samsung 2 Capital
Structure Analysis 2 Vodafone & Samsung Results 3 Liquidity analysis 3 Financial Leverage
Ratios 3 Possible changes in Capital Structure – Vodafone 4 Possible changes in Capital Structure –
Samsung 4 Capital Structure Finance Theories 4 Modigliani and Miller Irrelevancy Theory 4
Pecking Order Theory 4 Trade–off Theory 4 Clientele Effect 5 Traditional View &
Shareholders Wealth 5 Vodafone 5 Samsung 5 Bankruptcy Prediction Models 5 Univariate –
Beaver's Failure Ratios 5 Strengths & Weaknesses 5 Rationale 6 Multivariate – Altman's Z–
Score 6 Strengths & Weaknesses 6 Rationale 6 ... Show more content on Helpwriting.net ...
There is also no difference between the 2011 and the 2012 result, suggesting that Vodafone were not
interested in taking a larger proportion of debt INCLUDE SAMSUNG INFO AND COMPARE
WITH MARKET AVERAGES
The debt–to–equity ratio for Vodafone for the past 5 has constantly resulted in a ratio below 0.5.
This is a strong ratio for Vodafone, and permits a strong degree of protection for lenders. Again, the
ratios for 2011 and 2012 are almost identical, suggesting that Vodafone are currently happy with
their capital structure. INCLUDE SAMSUNG INFO AND COMPARE WITH MARKET
AVERAGES
Finally, Vodafone has a remarkably good ratio interest coverage ratio at 5.94, although this ratio has
been sporadic over the past 5 years with a high of 23.14 and a low of 2.73. It could be argued that
the current ratio, as well as the ratio from the previous year, are actually too high, indicating that
Vodafone is being too careful with the use of debt, which may mean lower risk, but also means
lower returns. INCLUDE SAMSUNG INFO AND COMPARE WITH MARKET AVERAGES
Overall, Vodafone has extremely good financial leverage ratios, which have all also been strong for
the past 5 years, indicating that Vodafone's

Default Risk And The Ways Of Identifying It Essay
Default Risk and the ways of identifying it in corporate bond market
Introduction
In bond market, there are a number of bonds offered for investors to purchase such as Treasury
bonds, municipal bonds, mortgage securities and so on. Among these various bonds, one particular
kind of bond is the corporate bond which attracts a wide range of investors with their higher return.
However, there are no free lunches in financial market. Being accompanied by the high yield, the
corporate bond investors have to face higher default risk which is the risk that the issuer will default
on its debt obligation in bond market. Especially after the 2008 crisis crunch in which vast amounts
of debt default occurred, an increasing number of investors realize the significance of identifying the
default risk in the bond investments. This essay will first consider the reason why investors ought to
recognize the default risk and secondly, will explore the different ways in which investors can
identify the default risk of corporate bonds.
Importance of recognizing default risk
In bond market, one important indicator of distinguishing the different bonds is the degree of default
risk. A good example of this is Treasury bonds and corporate bonds. These two bonds are similar in
the structure of coupon payment and the principal return, however, Treasury bonds generally may be
viewed as the free of default risk as we all know the government would not go bankruptcy easily,
which is a good option for

Racial Contact Theory
The article I chose to summarize is "Contact theory extended: The effects of prior racial contact on
the current social ties." The purpose of the study is that the psychologists want to address
methodological limitations in tests of contact theory. As well as how prior social contact with
interracial individuals at a young age, leads to those same individuals continuing to have friends that
are also interracial during adulthood. They also look further into behaviors and attitudes and how
they link to the contact theory. The methods used in this study included "the 1999–2000 Lilly
Survey of Attitudes and Social Networks, we conduct univariate and multivariate analyses to test
our hypotheses (Emerson et al. 2002)." The Lilly Survey of Attitudes

Millennium Cohort Study
RESULTS Overall, 108,129 Service members enrolled in panels 1 and 2 of the Millennium Cohort
Study and completed baseline survey. Service members who were not in active duty or National
Guard/Reserves at baseline (n=5,079), who did not remain in the assigned separation category until
end of study (n=37,922), who did not complete at least two follow–up surveys (n=27,984), and who
had missing covariate data (n=5,974) were excluded from the study. Exclusion criteria resulted in
31,170 study participants among whom approximately 18% (n=5,510) were categorized as veterans.
Majority of the study participants were male gender, aged 25–44, White, non–Hispanic, with less
than a bachelor's degree, married, and overweight. Veterans and Service ... Show more content on
Helpwriting.net ...
Furthermore, significant positive dose–response relationships were observed between smoking and
number of combat exposures as well as smoking and the amount of alcohol consumption. As stated,
time until separation, defined as time spent in Service between the completion of baseline survey
and date of separation, was further investigated among the veterans group (n=5,510). Table 3 shows
the results of the time until separation sub–analysis. The smoking prevalence were 23%, 20%, 20%,
and 17% for less than 3 months, 3 months to less than 1 year, 1 year to less than 2 years, and 2+
years, respectively. The differences of smoking prevalence by time until separation gradually
diminished over time after participants separated from service. By time 3, all groups had similar
smoking prevalence (12%–14%). At univariate level, a dose–response relationship was observed as
the closer participants were to the separation date at baseline, the higher chance of them being a
smoker. However, GEE model only revealed significantly elevated odds among those stayed in
service between 3 months to a year after the completion of baseline survey. For analyses examining
type of separation, we further excluded Reserve and National Guard personnel (n=1,658) due to the
lack of separation data. Table 4 shows smoking prevalence, unadjusted, and adjusted odds ratios of
smoking among

Diabetes Case Study
We did a prospective cross section study among type 2 diabetes patients with hypertension
comorbidity at Jimma University specialized Hospital (JUSH) from April 4 to May 11,2016. The
hospital is the only teaching and referral hospital in Southwestern part of Ethiopia. It provides
specialized health services for approximately 15,000 inpatient, 160,000 outpatient attendants a
year(29). The hospital ambulatory care clinic serves for 1700 type 2 diabetes and 2017 hypertensive
patients. Patients with diabetes and hypertension have regular follow up every month with possible
extension to every three months for some patients.
The study was approved by institutional review board of Jimma University. Letter of permission to
access data was ... Show more content on Helpwriting.net ...
To ensure the quality of the data, we trained data collectors; English version of the data collection
questionnaire was translated to Afan Oromo and Amharic and back translated to English. The data
collection tool was also pretested. The main outcome of this study was the presence of drug related
problems among type 2 diabetes patients with hypertension co–morbidity.
We included participants into the study Age ≥18 years old, T2DMPatients with hypertension
comorbidity, and patients who have were on treatment with anti–diabetic and anti–hypertensive
medications. The following participants were excluded from the study: patients not willing to
participate, patients with psychiatric comorbidity, and patients with incomplete medical records.
We used data abstraction format to collect data on diagnosis, duration of illness, dosage regimen of
medications, adverse drug reactions (ADRs) if any, diabetes complications, blood glucose and blood
pressure measurements, and laboratory results. Structured questionnaire was used to collect patients
'demographics, and patients' medication experience. Drug related problems (DRPs) and possible
causes of DRPs were identified using Cipolle's drug related problem identification tool (8, 15). The
appropriateness of drug indications, appropriateness of drug usage and dosage was assessed using
pharmacotherapy text book ninth edition and

Social Anxiety Disorder
I. Introduction
"Social anxiety disorder (SAD) involves an intense fear and avoidance of interpersonal situations
leading to significant distress and interfering with daily life." Social anxiety exists from the absence
of social fear, to ordinary social fear, to intense and functionally damaging social fear. High levels of
social anxiety in adolescents often lead to other serious disorders and are related to weak social
functioning. There is a relationship between social anxiety symptoms and self–image. Self–image is
the subjective perceptions about oneself in different aspects of life. Self–image is important during
adolescence since it is a time when individuals restructure their self and relationships. Social fear
has been strongly connected ... Show more content on Helpwriting.net ...
This had 130 items of self–description that measures 11 dimensions of adolescents' self–image. This
includes impulse control, emotional tone, body and self–image, social attitudes, ethical values,
vocational and educational goals, sexual attitudes, family relations, external mastery, psychological
health, and superior adjustment. The OSIQ items are scored on a Likert scale ranging from 1 (very
true of me) to 6 (not at all true of me). Higher scores indicated better adjustment and a positive self–
image (2). iii. Statistical analysis
Statistics were compiled for the observed variables. "Pearson's v2 and univariate ANOVA were used
to assess differences between groups, and a MANOVA was performed to examine the relationships
between social anxiety group and self–image dimensions while controlling for gender and age."
Logistic regression analyses were performed to predict the relationship between self–image and
social anxiety. A p–value of .05 was set for statistical significance (2).
III.

Analysis Of Bwi's Ad Campaign
In utilizing hypothesis testing, BWI's ad campaign that states the average airfares from BWI are
lower than averages fares from Dulles. The average (one–way) fares from Dulles over comparable
routes is claimed to be $165. If there is a 10% level of significance with over 100 degrees of
freedom, there is evidence that the mean sale price is actually not less than those at Dulles. In Figure
1, the t score equals –1.47. Therefore, the null must be rejected because the absolute value of T
(1.47) is greater than T of alpha (1.28) for the upper–tail test. The Dulles average fare of $165 is
greater than the average fares of BWI of $158.33 (from Figure 2). Average fares at BWI are actually
less than the fares at Dulles. Thus, because the null is rejected, there would be a Type I error. If the
null is rejected, but BWI accepts the null as true, then the Type I error would prove problematic. The
univariate estimate of fares in question previous aforementioned in the above statement, also known
as the point estimate method, can be improved by using another common type of univariate
estimation technique. In the point–estimate approach, we randomly choose a fare that would fall
under the range most of the fares in the data set fell under. Yet, the interval estimate method is more
accurate to use because point–estimate is technically impossible because probability at a specific
point is always zero. So, the interval estimates for the average fare with a 90% confidence level
would be

Dynamic Data Driven Selection Of Sensor Streams
On Dynamic Data–Driven Selection of Sensor Streams
This paper covers the online sensor selection in which the sensor network and relations between
sensors dynamically change by time and a model which is working for selection of sensors at time
may not work for the sensor selection at time , . The selection model of this paper is similar to
model discussed in section 3 (i.e. Online distributed sensor selection) but it is based on a well
defined special centralized algorithm (central server calculates the utility function and decides which
sensors should be selected).
The main goal of the sensor selection is to preserve battery by selecting a subset of sensors for
prediction. After the sensors have been selected, their value will be read in multiple turns (i.e. active
turns) and it will be used to predict the unselected sensors, then the value of all sensors will be read
(i.e. passive turn) and based on that the active set of the next interval will be selected. The art of this
paper is to find a way to switch between active and passive selection modes in some specific update
intervals (number of active turns before a passive turn) to find the optimized selection of sensors for
the next interval of data collection, this way it preserves the power requirement by activating only
few sensors for multiple turns and then trying to maintain the active set using the collected data of
the passive turns. It accomplishes this task by doing evaluation regression model over multiple

Psych 502 Data Set 2 Analysis
Psych 502 Data Set #2 Analysis It is not a good idea to treat this design as a completely crossed,
five–factor factorial design. Several independent variables might correlate with each other. Not
including a covariate in the model might cause unexplained variability that is associated with
variability in the covariate. As one can see in the table below, several factors correlate with each
other. There was a significant negative correlation between grade and gender, r=–.120, n=310,
p=.035, a significant negative correlation between Track and Gender, r=–.188, n=310, p=.001, and a
significant negative correlation between Track and Minority, r=–.273, n=310, p<.001, Treatment has
a significant effect on IQ8, F(5,309)= 6.760, p=.01, and Grade by ... Show more content on
Helpwriting.net ...
Std. Err. t–Value Sig. t Lower –95% CL– Upper 2 –2.3601651962 .90778 –2.59992 .00979 –
4.14667 –.57366 GRADE(1) Parameter Coeff. Std. Err. t–Value Sig. t Lower –95% CL–

A Multi Institutional Study Funded By The American Legacy...
Study 1 Sample As part of a multi–institutional study funded by the American Legacy Foundation
(ALF), 743 undergraduates self–identifying as Mexican–American were recruited from college
campuses in California, Florida, New York, and Texas. The primary aim of the overall study was to
compare smoking–related behaviors and attitudes across Hispanic subgroups (see American Legacy
Foundation, 2014; Hale, Perrotte, Baumann, & Garza, in press). Participants completed an online
survey requiring up to fifty minutes to complete. Questions included items pertaining to tobacco,
alcohol, and drug usage, as well as numerous trait and attitudinal measures. For Study 1, the sample
was composed of bicultural Mexican–American college students, operationalized as those who
scored 2.5 or higher on both domains of the BAS (Marín & Gamba, 1996). This resulted in a sample
of 335 individuals, which was further reduced to 309 when cases with missing data and outliers
were removed. Demographic information was collected as part of the survey. Fifty–five percent (n =
169) of the 309 respondents in the analyzed sample were female and 45% (n = 140) were male.
Approximately 69% of respondents (n = 212) reported that they were born in the United States,
while 27% (n = 85) indicated that they were born in Mexico; the remaining 4% (n = 12) indicated
that they were born in some other country or did not indicate a country of birth. Eighty–six percent
of respondents (n = 265) endorsed that they were

Factors Influencing The Adoption Behavior Of Coffee Producers
Selected explanatory variables
A micro–level approach was used in order to test which factors influence the adoption behavior of
coffee producers with regard to SMPs. The model incorporates farm and management
characteristics, the socioeconomic profile of producers and social capital indicators. Table 1 presents
the descriptive statistics of the data collected.
Several factors that were considered are accepted as common predictors of adoption in developing
countries. However, three questions related to explanatory variables were not included in the final
questionnaire. Firstly, we did not take into account access to bank loans since coffee farmers in
Mexico are mostly unable to obtain investment credit from lending institutions. Producers usually
have the option of obtaining short term financing (cash advances) either from local traders or from
coffee cooperatives for those who are members. However, the availability of long term credit has
virtually disappeared making it difficult for producers to defer the costs of implementing new
practices over several years (AMECAFE, 2009).
Secondly, tenure arrangements were not considered since households in the sampled area are
governed by a communal land resources committee, an institution independent of the municipality.
Under this system, producers hold usufruct rights to their coffee parcels. While a 1991 amendment
to the Mexican constitution made the privatization of communal lands (ejidos) possible it remains
the dominant type

How Does Low Blood Pressure Affecting Mortality?
1) Blood pressure: Blood pressure can be an important factor for predicting the mortality of patients.
In most of the cases, the blood pressure of the patients is generally recorded when the patients are
admitted to the hospitals. While conducting a study in UAE regarding factors affecting mortality it
was observed that patients who died had significantly lower GCS and systolic blood pressure on
arrival to hospital [6]. As per the study it was established that blood pressure was a significant factor
for predicting the mortality. A study conducting in Stockholm it was observed that low blood
pressure is directly related to mortality. Univariate chi–square tests showed that advanced age, male
sex, lower education, institutionalization, cancer,

Complications Of Functional Perception Patterns In The...
Introduction
The ability to generate category–related representations for a limitless collection of visual contents
is a vital function of human brain (Chao et al., 1999). It is demonstrated that widely–distributed
neural networks are engaged in the distinction of semantic categories, such as the ventral temporal
cortex, which plays a significant role in face and object recognition (Chao et al., 1999; Haxby et al.,
2000; Haxby et al., 2001; O'toole et al., 2005). Accumulating evidence has suggested that
differential neural response patterns in human brain are closely associated with specific categories of
visual stimuli (Haxby et al., 2000; Haxby et al., 2001; Kanwisher et al., 1997). However, it remains
unclear how the functional ... Show more content on Helpwriting.net ...
Using multi–voxel pattern analysis (MVPA), they found that the neural representations of face and
objects can be discriminated not only by activation patterns within the specific cortical regions that
maximally respond to one category, but can also be identified according to the patterns of
nonmaximal responses (Haxby et al., 2001), which provided us with novel insights into the neural
mechanism underlying the decoding of semantic categories.
While the MVPA method adopted in this study well characterized the features of the response
patterns associated with the semantic categories, it was computationally heavy. Also, it remained an
open question whether a simpler method–univariate analysis will provide sufficient evidence
indicating the category–specificity of the distributed neural representations in human brain.
Therefore, in the current study, I applied a straightforward univariate analysis on the original data of
Haxby et al.'s (2001) experiment to further investigate the neural response patterns evoked by face
and object stimuli. More specifically, I examined whether the category–related information was
revealed by the patterns of response across the whole brain space, and the activation in the
functional localizer fusiform face area resulted from face stimuli.
Methods
Subjects
Six subjects participated (5 females) in Haxby et

Immigration Status Essay
Manoj Banjara, Ph.D. Cleveland, OH 44120 (806) 316–1813; banjarm@hotmail.com Immigration
Status: Permanent Resident Summary ♣ 6+ years of experience in biostatistics with a demonstrated
history of working in hospitals, pharmaceutical, CRO, and healthcare industries as a biostatistical
SAS programmer. ♣ Involved in drug development process with exposure in analyzing and
reporting pre–clinical/clinical trial data. ♣ Good understanding of FDA submission (IND, NDA),
clinical protocols, CRFs, CDISC, ICH guidelines, 21 CFR Part 11, GCP guidelines, and IRB
guidelines. ♣ Experienced in SAS programming for importing and exporting huge datasets from flat
files, excel spreadsheets, and external Oracle RDBMS tables, LIBNAME, and SQL pass–through ...
Biostatistical Programmer– SGS Fairfield, NJ 4/2017–10/2017 ♣ Provided SAS programming and
analysis support for Alzheimer's Disease phase II clinical trials. ♣ Verified accuracy and integrity of
clinical data by performing validation checks written in SAS and data cleaning by examining data
related errors and missing values. ♣ Extensively used PROC SQL to retrieve, update, and report on
information from SAS data sets and other database products. ♣ Created new SAS programs and
modified existing programs using SAS/MACROS to make more efficient. ♣ Extensively used
procedures like PROC FREQ, PROC SORT, PROC TRANSPOSE, PROC FORMAT PROC
MEANS, PROC UNIVARIATE, PROC PRINTTO, and PROC COMPARE for data transformation,
manipulation, checking the assumptions, and conducting statistical analysis. ♣ Effectively
developed SAS conde for modeling data and implemented SAS/STAT procedures including PROC
ANOVA, PROC LIFETEST, PROC LIFEREG, PROC PHREG, PROC REG, and PROC GLM for

ANSWER TO MODULE 5 ASSIGNMENT Essay
Student Name
Professor Name
University
Date
Anxiety and Country
Answer:
This study examined differences in anxiety level between an industrial country and a nonindustrial
country. Anxiety is assessed three ways–cognitive, affective, and behavioral–with higher scores
indicating higher levels of the anxiety dimensions.
Directions:
Using the SPSS data file answer the following questions. NOTE: Helpful hints are provided here for
you to use while answering these questions.
1 What is the ONE independent variable in this study? What are the dependent variables?
The independent variable is COUNTRY (Industrial and Non–Industrial).
The dependent variables are Cognitive (COG), Affective (AFFECT) and Behavioral (BEHAVE).
2 ... Show more content on Helpwriting.net ...
It means that the distribution is right skewed because most values are concentrated on the left of the
mean, with extreme values to the right. The kurtosis value is 0.750 which is less than 3. It means
that distribution is Platykurtic because the probability for extreme values is less than for a normal
distribution, and the values are wider spread around the mean. The p–value for Shapiro–Wilk is
0.000 which is less than 0.05; it means that data is not normally distributed. The same result can be
obtained from the plot of Histogram.
For Behavioral variable, we can see that the mean is 7.8 with standard deviation as 2.28. The
skewness value is –0.919 which is smaller than 0. It means that the distribution is right skewed
because most values are concentrated on the left of the mean, with extreme values to the right. The
kurtosis value is 0.024 which is less than 3. It means that distribution is Platykurtic because the
probability for extreme values is less than for a normal distribution, and the values are wider spread
around the mean. The p–value for Shapiro–Wilk is 0.000 which is less than 0.05; it means that data
is not normally distributed. The same result can be obtained from the plot of Histogram.
5 Perform one–way between–subjects MANOVA on the data. Before interpreting the results of the
MANOVA, check outcomes that test other assumptions for this statistic: equality of covariance
matrices (see Box's Test) and

Teen Suicide Rates in Alaska
A Review of Temporal trends and geographic patterns of teen suicide in Alaska, 1979–1993.
Bradford D Gessner. Suicide & Life – Threatening Behavior. New York: Fall 1997. Vol. 27, Iss. 3;
pg. 264, 10 pgs
Temporal Trends and Geographic Patterns of Teen Suicide in Alaska, written by Bradford D.
Gessner, reported the findings of a study on teen suicide rates in Alaska. Using death certificates and
U.S. census data to record trends in suicide rates among Alaskan teens ages 14–19, it was found that
the teen suicide rate was 31.5 per 100,000 persons each year. The study tested three hypotheses, the
first being that the overall suicide rate of Alaska teens ages 14–19 during 1979–1993 would vary
according to residence, gender, race, and ... Show more content on Helpwriting.net ...
Gessner used correlational research (directly stated) in his study, as he examined the effect of
different variables. For example, the two variables teen suicide and gender were found to covary
together. "Besides determining suicide rates by census area, the correlation was determined between
these rates and several census area–level demographic variables." Correlational research involves
chi–square and linear regression tests – univariate, multivariate, and square root transformation – all
of which were used in this study. "Risk ratios and Taylor series 95% CIs as well as chisquare tests
for trend were calculated using Epi–Info computer software (Dean, Dean, Burton et al., 1995).
Linear regression analyses were conducted with SPSS (Norusis, 1993)." Descriptive research was
also employed in this study, as it involved the use of many statistics (e.g., suicide rate, number of
Alaska teens ages 14–19.) Obtaining information about the current status of various phenomena
allows one to describe what exists with

Cesarean Section: A Case Study
From a clinical perspective a cesarean delivery (Cesarean section or "C–section") is the delivery of
the baby through an incision in the abdomen and through an incision in the uterus. However, from a
maternal perspective, a cesarean is not just a routine medical procedure, it is the emotional, long–
anticipated arrival of an infant. According to the Centers for Disease Control and Prevention, almost
1/3 of all babies born in the United States are delivered surgically, making cesareans one of most
common operating room procedures. In recent years, some hospitals have begun to implement
small, but significant changes to the cesarean. The goal of the "gentle cesarean", sometimes also
referred to as "family–centered cesarean", is to make the procedure ... Show more content on
Helpwriting.net ...
Their research offers 5 years of practical experience and the best and largest sample size of 144. At
the urging of a statewide advocacy group, and because all available evidence suggests only benefits
and no known adverse outcomes from immediate skin–to–skin contact, their hospital, which is
associated with Brown University, was the first in the United States to implement gentle cesareans
as a standard of care. Based on my research, it appears that they are one of a very small number of
facilities that offer this standard of care today. Memorial Hospital of Rhode Island, where they
practice, developed a written protocol for gentle cesareans in 2009. The written protocol for their
gentle cesarean initiative was developed by a team of experts, and drew on existing strategies for
improving patient experience, as well as the team's experience in what would have the most impact
in their

Using Conditional Copula to Estimate Value Risk
Review: Using Conditional Copula to Estimate Value at Risk
ActSc 991 Project
Changwu (Allen) Chen April 14, 2014
1
1 Introduction
Value at Risk (VaR) plays a central role in risk management. By definition, VaR is the maximum
expected loss of a portfolio over a given time horizon with a certain confidence level. VaR can be
seen as a quantile on the lower tail of the distribution of portfolio returns. Although VaR is a simple
measure, it is not easily estimated.
There are several approaches for the estimation of VaR, such as historical simulations, the variance–
covariance, and the Monte Carlo approaches. The first approach does not assume any underlying
distribution, whereas the last two approaches demand the joint distribution to be known, which
frequently assumed to be normal distribution. However, the deviation from normality could lead to
an inadequate VaR estimate. In this case, the portfolio could be either riskier than desired or
unnecessarily conservative.
The theory of copula is a powerful tool in modelling multivariate distributions be– cause it does not
require the assumption of joint normality and it is a marginal free model. Copula have been broadly
used in the statistical literature. And due to its simplicity and convenience, one may be interested in
its application in the financial area.
In this paper I will first give a brief summary of the paper written by Helder Parra Palaro and Luiz
Koodi Hotta [1]. Then I will discuss the key results presented in the paper

Cen 225 Final Project
CENE 225
Statistics from Your Interest Area
Name: ___________________________________ (last, first)
You are all interested in something. Explore the literature (magazines, books, web sites, etc) for your
interest area and find an example of the use of graphical statistics. I suggest a Google search using
the Images option, and select some interesting and visual display of data. Identify the related
materials that support the graphic and containing some form of statistical analysis and/or display.
Review your materials using the framework offered below.
Attach copies of the material and highlight portions that support your analysis below.
Attach screen shots or print outs of enough of the material to support your analysis.
Add your answers to the blank areas below. Add more lines as necessary. ... Show more content on
Helpwriting.net ...
You must show that you have taken it apart enough to answer the questions. Please don't copy more
than a 2–3 pages of web material.
1. In a word or short phrase provide an identification (name) and brief explanation of the "random
variable" (or variables) considered in your statistical example.
Random Variable(s) Considered:
Ans: the random variable is being used in statistics and probability most of the time. This is also
called stochastic or aleatory variable as his has an ability of making its values vary according to the
subject or according to the chance that occur. A random variable has the ability of taking a set of
different kind of values that also have the different value with the value associated with it.
A statistical example for random variable is coin toss that refers to the discrete random variable as it
will get the outcomes in discrete number.
2. For each of the random variables considered identify its type:
(Nominal, Ordinal, Interval, Ratio) (See appropriate references for definitions)
Ans: these are the scales that are now described

An Study On Self Reported Recurrent Falls
Outcome Variable
The primary outcome for this study was self–reported recurrent falls in the previous twelve months
which is categorized base on the participants' response to the above two questions into: no fall,
single fall, and recurrent falls.
Independent Variables
The following variables based on the literature, were selected for this study:
1. Demographic variables: Age group (65–74; 75–84; 85 and older), Sex (Male; female), BMI
classification (Underweight; Normal weight; Overweight/Obese), Marital status (Married/Common
law; Widowed; Divorced/Separated; Single), Education (Less than secondary school; Secondary
school; Post–secondary).
2. General health & functional condition: Able to walk without help (Yes; No), Perceived health ...
Variables showing statistically significant associations with a p–value < 0.25 from the univariate
analysis were first examined for collinearity and then were entered into the multivariate analysis.
Using "Proc Surveylogistic", multinomial logistic regression models for the prediction of the single
fall and recurrent falls were conducted, considering non–fallers as the reference group. At every step
of the modeling process, a variable selection decision was made using alpha value of 0.05 as the
significance level [28]. When a variable was removed, testing for confounding by comparing the
values of the estimated regression coefﬁcients between the two models at each stage were carried
out. Any change in the regression coefficient values of 20% or more was considered an indication of
confounding and the variable was retained in the model. Based on the literature, all major
interactions among the variables in the model were tested, using 0.05 as the level of significance.
Finally, the predictive power of the model was evaluated using a Cox & Snell pseudo R–square [29].
Statistical tests were based on a two–tailed level of significance, with an alpha value of 0.05.
RESULTS
In tabulating, analyzing and reporting the results we adhered to the guidelines by Statistics Canada.
Therefore, all total

Reasons For Starbucks's Or Starbucks
Do you prefer Kaldi's or Starbucks? This choice is given to SIUE students every day. Our group
chose to conduct an experiment that proves that students prefer Starbucks to Kaldi's. To ensure we
got the best results, we created an eight–question survey, which we used as factors in our descriptive
statistics and regression outputs. They included: how old are you, what school are you in, what
gender are you, do you prefer Starbucks or Kaldi's, do you enjoy a treat with your drink, do you
prefer a store or out in the open, how many drinks do you get in a week, and what drives your
choice. To make sure we surveyed enough people, each of us had to survey 30 students which in
total, equaled up to 121, with an extra from one of us handing out 31 surveys.
Methodology
To execute surveying 121 SIUE students, we broke the campus up into fourths, consisting of the
Morris University Center, the Engineering Building, Founders, and Peck Hall. We ran into a
problem halfway through handing out surveys when, as a group, we decided to take out the
question, "How do you identify yourself?", because we felt it had no significance to our study. Once
we corrected our survey, we were able to input our data into Excel. When we first entered our data
into Excel, we had all of our questions going horizontal, with the different response options going
vertical. The total numbers of answers each question received was listed horizontally after the
question. On further investigation, our group found that

Econ
Preface In our data analysis we do some univariate analysis before proceeding to models. In survival
analysis it is highly recommended to look at the Kaplan–Meier curves for all the categorical
predictors. This will provide insight into the shape of the survival function for each group and give
an idea of whether or not the groups are proportional. We also consider the tests of equality across
strata to explore whether or not to include the predictor in the final model. For the categorical
variables such as marital, eservice, plusservice and totalservice we use the log–rank test of equality
across strata which is a non–parametric test. For the continuous variables such as age, address,
income, education, employment, and reside we use a ... Show more content on Helpwriting.net ...
Consequently we find the better model after dropping variables with the p–values more than 0.05.
Model 5 is the best model which has all the significant variables and has lowest AIC value of
1478.82 and BIC value of 1513.17. If the marital status is altered from married to unmarried, while
holding all other variables constant, the rate of churn decreases by (100% – 66.5%) = 33.5%. As
year in current address is increased by one year, all other variables are held constant, the rate of
churn decreases by (100% – 94.5%) = 5.5%. As year with current employer is increased by one year,
all other variables are held constant, the rate of churn decreases by (100% – 93.2%) = 6.8%. As
people switch from non eservice to e service, all other variables are held constant, the churn rate
decrease by (100% – 56.5%) = 43.5%. As people switch from non plusservice to plusservice, all
other variables are held constant, the churn rate decrease by (100% – 54.5%) = 45.5%. As education
level increases, all other variables are held constant, the churn rate increases by 12.83%. Finally, I
adjust my model for heteroscedasticity by using robust function. The final adjusted model is
presented below: Table 1: Final Model (Corrected for Heteroscedasticity) |Variable |Haz. Ratio
|Robust Standard Error |Z–value |Significant | |marital |0.665 |.0790557 |–3.43 |** |

Epidemiological Studies Essay
One of the most useful outcomes of studying epidemiology is learning how to evaluate critically the
scientific literature (Aschengrau & Seage, 2008). Critical assessment of this literature is an
important skill for public health professionals because the findings of epidemiologic research inform
so many activities (Aschengrau & Seage, 2008). Munnoch et al. (2008) done epidemiological
studies on S.Saintpaul infection occurred in Australia during October 2006 and found that
cantaloupe production and processing practices pose a potential public health threat requiring
regulatory and community education interventions. Based on main journal article written upon this
subject, this article will analyse how epidemiological research has helped us ... Show more content
on Helpwriting.net ...
According to Munnoch et al.2008 the objective of study was cleared that consumption of cantaloupe
was directly linked to the infection and hypothesis study done was relevant because it states that
cantaloupe was consumed more frequently by cases than expected when compared with the food
consumption data for controls from an Australian Campylobacter case–control study. So study
identified a strong epidemiological association between S.Saintapaul infection and consumption of
cantaloupe, with cases being 23 times more likely to have consumed cantaloupe in the 4 days prior
to onset of illness than controls. As there were so many people involved in the research so study
done was observational study, as no action was taken to change the health outcome – people were
simply "observed" (Webb & Bain, 2011). The study design used to measure in terms of hypothesis
generation method and observational study was useful.
STUDY PARAMETERS
Research exposure
Observational study design examined on the basis of exposure and health outcome. The exposure of
interest is the factor that either causes, Prevents, or treats the outcome. It is important to consider
whether the exposure was accurately defined and measured because exposure misclassification
stems from broad definitions and inaccurate measurements. (Aschengrau & Seage, 2008). According
to Munnoch et al. (2008), study conducted to investigate the S.Saintapaul infection

Study On Caffeine Consumption During College Students And...
Results
Univariate Demographic Analyses This study on caffeine consumption was conducted as a survey
given out to college students and an afterschool AP tutor class at Van Nuys High school. Of the
respondents, there were an equal amount of males and females (see Table 1). In total 55% of the
respondents were the high school students. The mean age was 18.28, 22 % of the respondents
currently in college. College graduates constitute 11 % of the participants. There was only 1
repondent who has a high school graduate and was not currently in college. Also, there was only 1
participant who was currently in grad school.
Table 1. Univariate Analysis of Demographic Variables, N=18. N %
Sex
Male Female
9
9
50
50
Age (mean in years) 18.28
Highest Level of Education Some High School High School Graduate Some College
Trade/technical/vocational training College Graduate Some Post Graduate Work Post Graduate
Degree
10
1
4
0
2
1
0
55.6
5.6
22
0.0
11.2
5.6
0.0

Univariate Research Analyses The amount of servings of caffeinated beverages consumed was one
of the most interesting measure I was concerned about. The mean for the amount of servings of
caffeinated beverages was 1.81 (seen in Table 2). Most participants had more than 1 serving and a
half a day. A serving is measured as 1 cup or 8 fluid ounces. My research also asked how much the
respondents agree or disagree that there were beneficial aspects of caffeine. With a scale of 4=
strongly agree,

Data Analysis : Correlation, Univariate And Multivariate...
2.4 Data Analysis: Correlation, Univariate and Multivariate regression models Multivariate
regression is a statistical tool used to predict the functional relationship between some dependent
variable and a set of independent variables [13, 14]. It comes as a generalization to simple univariate
regression models therefore it will be introduced accordingly. However selecting which variables
best influence the survival rate in LC is quite difficult. Out of 153 collected prognostic variables,
only few have a significant impact on the 5–year survival rate while the rest have almost no effect
other than complicating the model. Thus before implementing a neural network predictor we need to
sift through the variables to build a meaningful model and to that end several mathematical tools
were used including correlation analysis. Correlation is the degree of relationship between variables
and correlation analysis seeks to determine how well a linear or other equation describes or explains
the relationship between variables. If all values of the variables satisfy an equation exactly, we say
that the variables are perfectly correlated or that there is perfect correlation between them. Such
variables as the height and weight of individuals would show some correlation. When only two
variables are involved, we speak of simple correlation and simple regression. When more than two
variables are involved, we speak of multiple correlation and multiple regression. If X and Y denote
the two

A Study By Killen Et Al
A study by Killen et al. (1994) examined the level of weight and other variables associated with age
of onset of eating disorder symptoms over a 3–year interval in a community sample of young
adolescent girls. The objective of the experiment was to demonstrate the precursors of eating
disorder symptoms in a community sample of young adolescent girls. The hypothesis stated that
community based prospective studies are needed to understand what causes or influences the
development of eating disorders and identify variables that could prevent them. "In general, the line
of reasoning suggested by social learning explanations implicates prevailing social and cultural
norms in the development of eating disorders" (Killen et al., 1994, p. 228) .
Out of a total of 967 eligible sixth and seventh grade girls that were enrolled in four northern
California middle schools, 939 participated in the study. Of the 28 students that didn't participate, 19
refused and the rest were absent during assessments. Staff trained by principal investigators carried
out baseline and follow–up assessments. Students were assigned special identification numbers to
ensure confidentiality and for tracking purposes. Weight, height, dietary restraint, pubertal
development, body mass index (BMI), and behavior problems were measured and evaluated. An
Eating Disorder Inventory (EDI) and Youth Self–Report Inventory (YSI) were completed.
The independent variables were used in subsequent analyses: (1) EDI: combined

Related Literature Of Forx Rate
San Andres, Dan Carlo C. ENG 10 T–4R Review of Related Literature In today's economy, forex
rate, the price of one currency in terms of another, has considerably contributed to the economic
status of many countries all over the world. It is considered as one of the factors that identifies and
emphasizes the welfare of a country; specifically, the welfare of its residents. With forex rate, a
country can be provided with knowledge that may help them in different situations of interests.
(Wright, n.d.) According to Chand's article, forex rate has some major types. These are the
following: 1. Fixed Exchange Rate System – This system, also known as Pegged exchange rate
system, manages the steadiness of the exchange rate by fixing the exchange rate to a value of
another currency or to another valuable measure such as gold which is lead by the government.
However, even though it is a fixed exchange rate system, a small variation may still take place. 2.
Flexible Exchange Rate System – This system, also known as Floating exchange rate system, retains
the fluctuation of the currency's value depending on the foreign exchange market. This market
determines the exchange rate by the demand and ... Show more content on Helpwriting.net ...
With the help of VAR, the interrelationships among these macrovariables are determined. The
cointegration test was conducted to determine if there is an existing long run relationship among
variables and the Johansen's maximum likelihood method was used to estimate the vector of
cointegrated variables. Results showed that forward rate is one of the reasons to why exchange rates
move, the exchange rate and domestic real income has an inverse relation, and by variance
decomposition analysis, most of the changes in forex market are accounted to the exchange rate and
the forward

Completely Randomized Factorial Anova
Chapter 16
Completely Randomized Factorial ANOVA
This tutorial describes the procedures for computing F tests for a completely randomized factorial
analysis of variance design. The reading–speed data in Table 16.4–2 of the textbook are used to
illustrate the procedures.
1. Enter a description of the data in the SPSS Data Editor following steps 1–4 described in the
Frequency Distribution tutorial for Chapter 2. Use rows 1, 2, and 3 of the SPSS Data Editor Variable
View window to describe the two independent variables and the dependent variable. There are two
levels of room illumination, Illumination Level, denoted by a1 and a2. You identify the illumination
levels in the Values cell of the Variable View window. When you click on ... Show more content on
Helpwriting.net ...
Next, click on Tukey to select this multiple comparison procedure. The preferred procedure, Fisher–
Hayter statistic, is not an option in SPSS. When the n's are equal, the Tukey and Fisher–Hayter
statistics are equal. You can compute the Fisher–Hayter statistic from the information in the ANOVA
and Multiple Comparisons tables given later. The Fisher–Hayter statistic can be referred to the
Studentized Range table (Table D9) in your textbook to obtain a slightly more powerful test. Click
on the Continue button to return to the Univariate window.
11. In the Univariate window, click on the Options button to bring up the Univariate: Options
window shown here.
[pic]
12. Select (Overall) in the Factor(s) and Factor Interactions box and click on the arrow beside the
Display Means for box. This moves (Overall) into the Display Means for box. Repeat the procedure
for I_level, T_size, and I_level*T_size. Next, click on the Descriptive Statistics box, Estimates of
effect size box, and the Homogeneity tests box. Then click on the Continue button to return to the
Univariate window. Click on the OK button in the Univariate window to obtain the ANOVA output
shown here.
[pic]
[pic]

[pic]
[pic]
[pic]
[pic]
[pic]
[pic]
[pic]
[pic]
13. The Between–Subjects Factors window displays the number of observation in each level of the
two independent variables.
The Descriptive Statistics window displays the mean, standard deviation, and sample size for

Pediatric Sarcomas Form A Heterogeneous Group Of...
Pediatric sarcomas form a heterogeneous group of mesenchymal skeletal and extraskeletal
malignancies [1]. Over the last few decades a multimodal treatment approach has improved
dramatically the prognosis for children with localized Ewing sarcomas (EWS) and
rhabdomyosarcoma (RMS) (65–70% event–free survival rate) [2, 3]. Though EWS and RMS are
considered radiosensitive, the proportion of patients whose primary tumors are treated with
external–beam radiotherapy (EBRT) alone has steadily declined over the past 30 years [4]. Increased
awareness of the late effects of radiotherapy (particularly second malignancies and growth
disturbances) and advances in imaging and orthopedic surgery has increased the use of surgical
management for these tumors [5]. Due to the fact that complete resection is often difficult or morbid
to perform, adjuvant EBRT still plays an important role in local control (LC) promotion [2, 3]. The
challenge of achieving LC with a suitable therapeutic ratio is especially demanding in the pediatric
population and results in a very narrow therapeutic window in which to balance benefits and late
effects. The known detrimental effects of irradiating large volumes with EBRT, impulsed limited
radiation therapy alternatives such us intraoperative radiation therapy (IORT) as an adapted
technical opportunity to be explored in innovative practice [6]. Several collaborative groups are
trying to determine the optimal radiation therapy dose and volume necessary to further

Federal Regulation Of The United States On The Volatility...
1. Introduction
This paper examines the impact of federal regulation in the United States on the volatility of stock
returns for firms in different segments of the financial service industry. I examine the volatility of
stock returns for banks, savings associations, securities firms and insurance companies. Moreover, I
compare the volatility dependence of stock returns for these segments with the introduction of new
federal regulation, specifically the Dodd–Frank Wall Street Reform and Consumer Protection Act in
2010 (Dodd–Frank Act).
Regulation of financial markets is very significant for investors in the stock markets, policy–makers,
practitioners, and academicians who explore the topic very rigorously. This paper contributes to the
field by examining the volatility among stock returns for firms in different segments of the financial
services industry. My findings are useful to investors and have significant implication for policy–
makers and federal regulators in the United States.
The Dodd–Frank Wall Street Reform and Consumer Protection Act of 2010 (Dodd–Frank) is the
recent federal legislation that was enacted following the 2008–2009 global financial crisis that some
have deemed as "the worst financial crisis since the Great Depression". Regulatory reform of the
financial system is an urgent priority as the recent financial crisis exposed some of the fundamental
weaknesses in the financial regulatory system of the United States (Wilmarth, 2011). The response
of

Data Matrix Of Cpi Data Distribution After Transformation...

More Related Content

Similar to Data Matrix Of Cpi Data Distribution After Transformation... (9)

More from Kimberly Jones (20)

Recently uploaded (20)

Data Matrix Of Cpi Data Distribution After Transformation...