Statistics-MAEd-Module-1-FINAL PRESENTATION

STATISTICS WITH
COMPUTER APPLICATION
Prepared by: Neil Arden B. Sotto

Module 1
Basic Concepts
Definition of Statistics
Role of Statistics in Research
Sources of Data
Types of Data
Methods of Collecting and
Presenting Data
MODULE 1 – OVERVIEW SOTTO, N.A. (2024)

The term STATISTICS is used in either singular
or plural sense.
In its singular sense, Statistics refers to the
principles and methods of handling or
processing data. These methods range from the
most basic (mean, median, and mode) to those
extremely complicated mathematical
procedure (T-tests, Chi Square, ANOVA, etc.)
MODULE 1 – DEFINITION OF STATISTICS SOTTO, N.A. (2024)

The term STATISTICS is used in either singular
or plural sense.
In its plural sense, statistics refer to a body of
numerical facts of any kind (i.e. athletic stats,
vital stats, etc.)

STATISTICS deals with collecting,
presenting, analyzing, and
interpreting numerical or quantitative
data.

 It is used by researchers in many fields to collect, organize,
summarize, analyze, interpret, and present data in a meaningful
and convenient way.
 It will enable researchers to give exact descriptions of the
collected data in his/her research
 It enables researchers to develop accurate and reasonable
inferences from the relevant data he/she collected.
MODULE 1 – ROLE OF STATISTICS IN RESEARCH SOTTO, N.A. (2024)

 Knowledge on statistics would enable the researchers and
consumers of research to evaluate the credibility and usefulness
of information derived from the data, for them to make
appropriate decisions or actions based on the data collected
 Results acquired from research are meaningless raw data
unless analyzed with the appropriate statistical tool. Therefore,
determining statistics in research is of utmost necessity to justify
research findings.
MODULE 1 – ROLE OF STATISTICS IN RESEARCH SOTTO, N.A. (2024)

Sources of Data
 Primary Data – firsthand data collected from the source
(informants, respondents, or records) by the researcher himself
 Secondary Data – data taken from published material or
compiled by the researcher, organization, research institution,
and other agencies. Sometimes referred to as “archival data”.
MODULE 1 – SOURCES OF DATA SOTTO, N.A. (2024)

Main Types of Data
 Qualitative Data – is a categorical measurement expressed
not in terms of numbers, but rather by verbal description. In
statistics, it is often used interchangeably with “categorical”
data.
 Quantitative Data – is a numerical measurement acquired
through counting or measuring.
MODULE 1 – TYPES OF DATA SOTTO, N.A. (2024)

Types of Quantitative / Numerical Data
 Discrete – can only take particular value e.g. number of
students in a class, number of languages a person speaks,
number of family members in a household, number of voters in
a barangay; you can’t have a fraction of this data. (ex. 34, 10)
 Continuous – not restricted and can occupy any value over a
continuous range such as weight, height, length, temperature
(ex. 42.8 kg, 6.72 meters, 32.5°C)

(based on the Level of Measurement)
Levels of Measurement, also called scales of measurement, tell
us how precisely variables or data are recorded.
There are 4 Levels of Measurement:
• Nominal – numerical assignment as identifiers only
• Ordinal – categorized and ranked
• Interval – difference is evident and no true zero point
• Ratio – has a true zero point

1. Nominal – categorical data in which numbers are simply used
as identifiers, a number assigned for classification or
identification purposes only and does not have quantitative
meaning.
Example: 1 – male 2 – female
*sex, marital status, religious affiliation, race

2. Ordinal – ranked data used to classify and order classes.
Example: Likert – type questions answerable by
(5) – Very Highly Satisfied
(4) – Highly Satisfied
(3) – Moderately Satisfied
(2) – Dissatisfied
(1) – Very Dissatisfied

3. Interval – is a measurement where the difference between
two values is meaningful. Interval scales are numeric scales in
which we know not only the order, but also the exact
differences between the values. In particular, interval data
has no true zero point.
Example: temperature (°C & °F), IQ, calendar years

4. Ratio – the highest level of measurement, has “true zero” and
therefore provide absolute magnitude of attribute.
True zero means that a value of zero signifies total absence
of the variable of interest.
Example: height, weight, length, area, speed, age, time

Methods of Collecting Data
 Interview – a person to person exchange of information. Uses
interview schedule or guide questionnaire.
 Questionnaire – a set of prepared questions to be answered
by the respondents.
 Experiment – conduct of an activity to obtain results
 Observation – recording of naturally occurring observable
data.
MODULE 1 – METHODS OF COLLECTING DATA SOTTO, N.A. (2024)

Methods of Presenting Data
 Textual - narrative form
 Tabular - arranging or summarizing data in statistical tables
 Graphical – use of graphs such as pie, bar, line, pictograph and
other graphical illustrations.
MODULE 1 – METHODS OF PRESENTING DATA SOTTO, N.A. (2024)

MODULE 1 – METHODS OF PRESENTING DATA SOTTO, N.A. (2024)

REFERENCES:
1. SPSS Tutorial (The Basics, Data, Descriptive Statistics, Chi-
square and T-tests, Correlation and Regression, One-way
ANOVA and Factorial ANOVA),
www.Psych.utoronto.ca/courses/c1/spss/toc.htm
2. Raynald’s SPSS Tools, SPSS Tutorials,
www.SPSStools.net/spss.htm
SOTTO, N.A. (2024)
MODULE 1 – REFERENCES

REFERENCES:
3. SPSS Tutorial 1-You Tube, Qassim Medical College
www.youtube.com/watch?v=ZsjQht9TaOk
4. Dr. Asma Ali, Hands-on Tutorial on IBM SPSS Software,
www.youtube.com/playlist?list
5. Amherst College, SPSS Tutorial, ANOVA with Repeated
Measures, Basic SPSS Instructions on Chi-Square Goodness
of Fit and Test of Independence , www.amherst.edu
SOTTO, N.A. (2024)

REFERENCES:
6. Laerd Statistics: SPSS Tutorial and Statistical Guides, for
Statistics Courses, Dissertations/theses and Research
Projects. https://statistics.laerd.com/
7. SPSS Tutorial – Harvard-MIT Data Center-Harvard
University, www.hmdc.harvard.edu
8. SPSS Online Training Workshop- Mathematics Department
Calcnet.mth.cmich.edu/org/spss/toc.htm
SOTTO, N.A. (2024)

Statistics-MAEd-Module-1-FINAL PRESENTATION

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