SlideShare a Scribd company logo
1
Chapter 1: Introduction to
Statistics
2
Variables
• A variable is a characteristic or condition
that can change or take on different
values.
• Most research begins with a general
question about the relationship between
two variables for a specific group of
individuals.
3
Population
• The entire group of individuals is called the
population.
• For example, a researcher may be
interested in the relation between class
size (variable 1) and academic
performance (variable 2) for the population
of third-grade children.
4
Sample
• Usually populations are so large that a
researcher cannot examine the entire
group. Therefore, a sample is selected to
represent the population in a research
study. The goal is to use the results
obtained from the sample to help answer
questions about the population.
Chapter1
6
Types of Variables
• Variables can be classified as discrete or
continuous.
• Discrete variables (such as class size)
consist of indivisible categories, and
continuous variables (such as time or
weight) are infinitely divisible into whatever
units a researcher may choose. For
example, time can be measured to the
nearest minute, second, half-second, etc.
7
Real Limits
• To define the units for a continuous
variable, a researcher must use real limits
which are boundaries located exactly half-
way between adjacent categories.
8
Measuring Variables
• To establish relationships between
variables, researchers must observe the
variables and record their observations.
This requires that the variables be
measured.
• The process of measuring a variable
requires a set of categories called a scale
of measurement and a process that
classifies each individual into one
category.
9
4 Types of Measurement Scales
1. A nominal scale is an unordered set of
categories identified only by name.
Nominal measurements only permit you
to determine whether two individuals are
the same or different.
2. An ordinal scale is an ordered set of
categories. Ordinal measurements tell
you the direction of difference between
two individuals.
10
4 Types of Measurement Scales
3. An interval scale is an ordered series of equal-
sized categories. Interval measurements
identify the direction and magnitude of a
difference. The zero point is located arbitrarily
on an interval scale.
4. A ratio scale is an interval scale where a value
of zero indicates none of the variable. Ratio
measurements identify the direction and
magnitude of differences and allow ratio
comparisons of measurements.
11
Correlational Studies
• The goal of a correlational study is to
determine whether there is a relationship
between two variables and to describe the
relationship.
• A correlational study simply observes the
two variables as they exist naturally.
Chapter1
13
Experiments
• The goal of an experiment is to
demonstrate a cause-and-effect
relationship between two variables; that is,
to show that changing the value of one
variable causes changes to occur in a
second variable.
14
Experiments (cont.)
• In an experiment, one variable is manipulated
to create treatment conditions. A second
variable is observed and measured to obtain
scores for a group of individuals in each of the
treatment conditions. The measurements are
then compared to see if there are differences
between treatment conditions. All other
variables are controlled to prevent them from
influencing the results.
• In an experiment, the manipulated variable is
called the independent variable and the
observed variable is the dependent variable.
Chapter1
16
Other Types of Studies
• Other types of research studies, know as
non-experimental or quasi-
experimental, are similar to experiments
because they also compare groups of
scores.
• These studies do not use a manipulated
variable to differentiate the groups.
Instead, the variable that differentiates the
groups is usually a pre-existing participant
variable (such as male/female) or a time
variable (such as before/after).
17
Other Types of Studies (cont.)
• Because these studies do not use the
manipulation and control of true
experiments, they cannot demonstrate
cause and effect relationships. As a
result, they are similar to correlational
research because they simply
demonstrate and describe relationships.
Chapter1
19
Data
• The measurements obtained in a research
study are called the data.
• The goal of statistics is to help researchers
organize and interpret the data.
20
Descriptive Statistics
• Descriptive statistics are methods for
organizing and summarizing data.
• For example, tables or graphs are used to
organize data, and descriptive values such
as the average score are used to
summarize data.
• A descriptive value for a population is
called a parameter and a descriptive
value for a sample is called a statistic.
21
Inferential Statistics
• Inferential statistics are methods for using
sample data to make general conclusions
(inferences) about populations.
• Because a sample is typically only a part of the
whole population, sample data provide only
limited information about the population. As a
result, sample statistics are generally imperfect
representatives of the corresponding population
parameters.
22
Sampling Error
• The discrepancy between a sample
statistic and its population parameter is
called sampling error.
• Defining and measuring sampling error is
a large part of inferential statistics.
Chapter1
24
Notation
• The individual measurements or scores obtained
for a research participant will be identified by the
letter X (or X and Y if there are multiple scores
for each individual).
• The number of scores in a data set will be
identified by N for a population or n for a sample.
• Summing a set of values is a common operation
in statistics and has its own notation. The Greek
letter sigma, Σ, will be used to stand for "the sum
of." For example, ΣX identifies the sum of the
scores.
25
Order of Operations
1. All calculations within parentheses are done
first.
2. Squaring or raising to other exponents is done
second.
3. Multiplying, and dividing are done third, and
should be completed in order from left to right.
4. Summation with the Σ notation is done next.
5. Any additional adding and subtracting is done
last and should be completed in order from left
to right.

More Related Content

PPTX
1 introduction to psychological statistics
PPTX
Workshop on Data Analysis and Result Interpretation in Social Science Researc...
PDF
Student's T Test
PDF
PPTX
t-test vs ANOVA
PDF
Analysis of Variance (ANOVA)
PPTX
Workshop on Data Analysis and Result Interpretation in Social Science Researc...
1 introduction to psychological statistics
Workshop on Data Analysis and Result Interpretation in Social Science Researc...
Student's T Test
t-test vs ANOVA
Analysis of Variance (ANOVA)
Workshop on Data Analysis and Result Interpretation in Social Science Researc...

What's hot (19)

PPTX
Non Parametric Tests
PPTX
PPTX
Statistical analysis
PPTX
Statistical tests
PPTX
F test and ANOVA
PPTX
Non parametric test 8
PPTX
Repeated anova measures ppt
PPTX
DATA PROCESSING AND STATISTICAL TREATMENT
PPTX
The mann whitney u test
PPTX
Anova in easyest way
PDF
Problems statistics 1
PPTX
Statistical treatment and data processing copy
PPTX
Parametric and Non Parametric methods
PPTX
3.1 non parametric test
PPTX
Parametric test 7
PPTX
Assignment AW
PPTX
Parametric & non-parametric
PDF
Aca 22-407
PPTX
Parametric Statistical tests
Non Parametric Tests
Statistical analysis
Statistical tests
F test and ANOVA
Non parametric test 8
Repeated anova measures ppt
DATA PROCESSING AND STATISTICAL TREATMENT
The mann whitney u test
Anova in easyest way
Problems statistics 1
Statistical treatment and data processing copy
Parametric and Non Parametric methods
3.1 non parametric test
Parametric test 7
Assignment AW
Parametric & non-parametric
Aca 22-407
Parametric Statistical tests
Ad

Similar to Chapter1 (20)

PPT
Introduction to statistics
PDF
STATISTICS FOR HEALTH PROFESSIONALS.pdf HS
PPTX
Chapter_1_Lecture.pptx
PPT
chapter1-introduction and presentation.ppt
PPTX
Introduction to Statistics
PDF
1. Review Statistics and Probability.pdf
PDF
STA 204. 200 level university of Ibadan statistics department
PPT
1. Biost. Introduction(2).ppt
PPTX
Introduction to Statistics Presentation.pptx
PPTX
Biostatistics ppt itroductionchapter 1.pptx
PPTX
Introduction-to-Statistics.pptx
PPT
Chapter 1
PPTX
Unit #1.Introduction to Biostatistics.pptx
PPTX
Research Methodology
PPT
Stats-Review-Maie-St-John-5-20-2009.ppt
PPTX
Introduction to statistics.pptx
PPTX
Introduction to Statistics statistics formuls
PPTX
introductiontostatisticsanddatareasoningupdated.pptx
PDF
Data Analysis with SPSS PPT.pdf
PDF
THE BASIC CONCEPTS OF STATISTICS REVIEW.pdf
Introduction to statistics
STATISTICS FOR HEALTH PROFESSIONALS.pdf HS
Chapter_1_Lecture.pptx
chapter1-introduction and presentation.ppt
Introduction to Statistics
1. Review Statistics and Probability.pdf
STA 204. 200 level university of Ibadan statistics department
1. Biost. Introduction(2).ppt
Introduction to Statistics Presentation.pptx
Biostatistics ppt itroductionchapter 1.pptx
Introduction-to-Statistics.pptx
Chapter 1
Unit #1.Introduction to Biostatistics.pptx
Research Methodology
Stats-Review-Maie-St-John-5-20-2009.ppt
Introduction to statistics.pptx
Introduction to Statistics statistics formuls
introductiontostatisticsanddatareasoningupdated.pptx
Data Analysis with SPSS PPT.pdf
THE BASIC CONCEPTS OF STATISTICS REVIEW.pdf
Ad

More from AndresBrutas (11)

PPTX
Conceptual framework of mathematics
PPT
Measure of central tendency (2)
PPTX
Understanding cooperative-learning-structure-cls (1)
PPTX
Flipping the-classroom
PPTX
5 e`s model ppt
PPT
Critical thinking-basics-ppt
PPTX
Conceptual framework of mathematics
PPT
Critical thinking-basics-ppt
PPTX
Conceptual framework of mathematics
PPTX
Problem solving
PPTX
Chapter 2-nstp-the-philippine-constitution (1)
Conceptual framework of mathematics
Measure of central tendency (2)
Understanding cooperative-learning-structure-cls (1)
Flipping the-classroom
5 e`s model ppt
Critical thinking-basics-ppt
Conceptual framework of mathematics
Critical thinking-basics-ppt
Conceptual framework of mathematics
Problem solving
Chapter 2-nstp-the-philippine-constitution (1)

Recently uploaded (20)

PDF
Complications of Minimal Access Surgery at WLH
PPTX
Pharmacology of Heart Failure /Pharmacotherapy of CHF
PDF
Module 4: Burden of Disease Tutorial Slides S2 2025
PPTX
Microbial diseases, their pathogenesis and prophylaxis
PDF
Physiotherapy_for_Respiratory_and_Cardiac_Problems WEBBER.pdf
PPTX
Institutional Correction lecture only . . .
PPTX
Pharma ospi slides which help in ospi learning
PDF
3rd Neelam Sanjeevareddy Memorial Lecture.pdf
PPTX
human mycosis Human fungal infections are called human mycosis..pptx
PPTX
BOWEL ELIMINATION FACTORS AFFECTING AND TYPES
PDF
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
PDF
STATICS OF THE RIGID BODIES Hibbelers.pdf
PDF
O7-L3 Supply Chain Operations - ICLT Program
PDF
2.FourierTransform-ShortQuestionswithAnswers.pdf
PDF
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
PDF
Basic Mud Logging Guide for educational purpose
PPTX
Renaissance Architecture: A Journey from Faith to Humanism
PDF
Classroom Observation Tools for Teachers
PDF
Insiders guide to clinical Medicine.pdf
PDF
Business Ethics Teaching Materials for college
Complications of Minimal Access Surgery at WLH
Pharmacology of Heart Failure /Pharmacotherapy of CHF
Module 4: Burden of Disease Tutorial Slides S2 2025
Microbial diseases, their pathogenesis and prophylaxis
Physiotherapy_for_Respiratory_and_Cardiac_Problems WEBBER.pdf
Institutional Correction lecture only . . .
Pharma ospi slides which help in ospi learning
3rd Neelam Sanjeevareddy Memorial Lecture.pdf
human mycosis Human fungal infections are called human mycosis..pptx
BOWEL ELIMINATION FACTORS AFFECTING AND TYPES
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
STATICS OF THE RIGID BODIES Hibbelers.pdf
O7-L3 Supply Chain Operations - ICLT Program
2.FourierTransform-ShortQuestionswithAnswers.pdf
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
Basic Mud Logging Guide for educational purpose
Renaissance Architecture: A Journey from Faith to Humanism
Classroom Observation Tools for Teachers
Insiders guide to clinical Medicine.pdf
Business Ethics Teaching Materials for college

Chapter1

  • 2. 2 Variables • A variable is a characteristic or condition that can change or take on different values. • Most research begins with a general question about the relationship between two variables for a specific group of individuals.
  • 3. 3 Population • The entire group of individuals is called the population. • For example, a researcher may be interested in the relation between class size (variable 1) and academic performance (variable 2) for the population of third-grade children.
  • 4. 4 Sample • Usually populations are so large that a researcher cannot examine the entire group. Therefore, a sample is selected to represent the population in a research study. The goal is to use the results obtained from the sample to help answer questions about the population.
  • 6. 6 Types of Variables • Variables can be classified as discrete or continuous. • Discrete variables (such as class size) consist of indivisible categories, and continuous variables (such as time or weight) are infinitely divisible into whatever units a researcher may choose. For example, time can be measured to the nearest minute, second, half-second, etc.
  • 7. 7 Real Limits • To define the units for a continuous variable, a researcher must use real limits which are boundaries located exactly half- way between adjacent categories.
  • 8. 8 Measuring Variables • To establish relationships between variables, researchers must observe the variables and record their observations. This requires that the variables be measured. • The process of measuring a variable requires a set of categories called a scale of measurement and a process that classifies each individual into one category.
  • 9. 9 4 Types of Measurement Scales 1. A nominal scale is an unordered set of categories identified only by name. Nominal measurements only permit you to determine whether two individuals are the same or different. 2. An ordinal scale is an ordered set of categories. Ordinal measurements tell you the direction of difference between two individuals.
  • 10. 10 4 Types of Measurement Scales 3. An interval scale is an ordered series of equal- sized categories. Interval measurements identify the direction and magnitude of a difference. The zero point is located arbitrarily on an interval scale. 4. A ratio scale is an interval scale where a value of zero indicates none of the variable. Ratio measurements identify the direction and magnitude of differences and allow ratio comparisons of measurements.
  • 11. 11 Correlational Studies • The goal of a correlational study is to determine whether there is a relationship between two variables and to describe the relationship. • A correlational study simply observes the two variables as they exist naturally.
  • 13. 13 Experiments • The goal of an experiment is to demonstrate a cause-and-effect relationship between two variables; that is, to show that changing the value of one variable causes changes to occur in a second variable.
  • 14. 14 Experiments (cont.) • In an experiment, one variable is manipulated to create treatment conditions. A second variable is observed and measured to obtain scores for a group of individuals in each of the treatment conditions. The measurements are then compared to see if there are differences between treatment conditions. All other variables are controlled to prevent them from influencing the results. • In an experiment, the manipulated variable is called the independent variable and the observed variable is the dependent variable.
  • 16. 16 Other Types of Studies • Other types of research studies, know as non-experimental or quasi- experimental, are similar to experiments because they also compare groups of scores. • These studies do not use a manipulated variable to differentiate the groups. Instead, the variable that differentiates the groups is usually a pre-existing participant variable (such as male/female) or a time variable (such as before/after).
  • 17. 17 Other Types of Studies (cont.) • Because these studies do not use the manipulation and control of true experiments, they cannot demonstrate cause and effect relationships. As a result, they are similar to correlational research because they simply demonstrate and describe relationships.
  • 19. 19 Data • The measurements obtained in a research study are called the data. • The goal of statistics is to help researchers organize and interpret the data.
  • 20. 20 Descriptive Statistics • Descriptive statistics are methods for organizing and summarizing data. • For example, tables or graphs are used to organize data, and descriptive values such as the average score are used to summarize data. • A descriptive value for a population is called a parameter and a descriptive value for a sample is called a statistic.
  • 21. 21 Inferential Statistics • Inferential statistics are methods for using sample data to make general conclusions (inferences) about populations. • Because a sample is typically only a part of the whole population, sample data provide only limited information about the population. As a result, sample statistics are generally imperfect representatives of the corresponding population parameters.
  • 22. 22 Sampling Error • The discrepancy between a sample statistic and its population parameter is called sampling error. • Defining and measuring sampling error is a large part of inferential statistics.
  • 24. 24 Notation • The individual measurements or scores obtained for a research participant will be identified by the letter X (or X and Y if there are multiple scores for each individual). • The number of scores in a data set will be identified by N for a population or n for a sample. • Summing a set of values is a common operation in statistics and has its own notation. The Greek letter sigma, Σ, will be used to stand for "the sum of." For example, ΣX identifies the sum of the scores.
  • 25. 25 Order of Operations 1. All calculations within parentheses are done first. 2. Squaring or raising to other exponents is done second. 3. Multiplying, and dividing are done third, and should be completed in order from left to right. 4. Summation with the Σ notation is done next. 5. Any additional adding and subtracting is done last and should be completed in order from left to right.