SlideShare a Scribd company logo
1 of 25
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.
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.
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.
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.
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.
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

Similar to chapter1.ppt

7- Quantitative Research- Part 3.pdf
7- Quantitative Research- Part 3.pdf7- Quantitative Research- Part 3.pdf
7- Quantitative Research- Part 3.pdfezaldeen2013
 
Introduction to research
Introduction to researchIntroduction to research
Introduction to researchANCYBS
 
TYPESOFDATAANALYSIS research methodology .pdf
TYPESOFDATAANALYSIS research methodology .pdfTYPESOFDATAANALYSIS research methodology .pdf
TYPESOFDATAANALYSIS research methodology .pdfMounika711622
 
When to use, What Statistical Test for data Analysis modified.pptx
When to use, What Statistical Test for data Analysis modified.pptxWhen to use, What Statistical Test for data Analysis modified.pptx
When to use, What Statistical Test for data Analysis modified.pptxAsokan R
 
Statistics for Data Analytics
Statistics for Data AnalyticsStatistics for Data Analytics
Statistics for Data AnalyticsSSaudia
 
satatistics Presentation.pptx
satatistics Presentation.pptxsatatistics Presentation.pptx
satatistics Presentation.pptxMdMatiurRahman25
 
Biostatistics and Research Methodology Semester 8
Biostatistics and Research Methodology Semester 8Biostatistics and Research Methodology Semester 8
Biostatistics and Research Methodology Semester 8ParulSharma130721
 
Multivariate Variate Techniques
Multivariate Variate TechniquesMultivariate Variate Techniques
Multivariate Variate TechniquesDr. Keerti Jain
 
Selection of appropriate data analysis technique
Selection of appropriate data analysis techniqueSelection of appropriate data analysis technique
Selection of appropriate data analysis techniqueRajaKrishnan M
 
Introduction to Statistics
Introduction to StatisticsIntroduction to Statistics
Introduction to Statisticsjasondroesch
 
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxBASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxardrianmalangen2
 
tests of significance
tests of significancetests of significance
tests of significancebenita regi
 

Similar to chapter1.ppt (20)

1 introduction to psychological statistics
1 introduction to psychological statistics1 introduction to psychological statistics
1 introduction to psychological statistics
 
PR 2, WEEK 2.pptx
PR 2, WEEK 2.pptxPR 2, WEEK 2.pptx
PR 2, WEEK 2.pptx
 
7- Quantitative Research- Part 3.pdf
7- Quantitative Research- Part 3.pdf7- Quantitative Research- Part 3.pdf
7- Quantitative Research- Part 3.pdf
 
Introduction to research
Introduction to researchIntroduction to research
Introduction to research
 
TYPESOFDATAANALYSIS research methodology .pdf
TYPESOFDATAANALYSIS research methodology .pdfTYPESOFDATAANALYSIS research methodology .pdf
TYPESOFDATAANALYSIS research methodology .pdf
 
When to use, What Statistical Test for data Analysis modified.pptx
When to use, What Statistical Test for data Analysis modified.pptxWhen to use, What Statistical Test for data Analysis modified.pptx
When to use, What Statistical Test for data Analysis modified.pptx
 
Research
ResearchResearch
Research
 
Statistics for Data Analytics
Statistics for Data AnalyticsStatistics for Data Analytics
Statistics for Data Analytics
 
PR 2, WEEK 2.pptx
PR 2, WEEK 2.pptxPR 2, WEEK 2.pptx
PR 2, WEEK 2.pptx
 
Chapter02
Chapter02Chapter02
Chapter02
 
Chapter02
Chapter02Chapter02
Chapter02
 
satatistics Presentation.pptx
satatistics Presentation.pptxsatatistics Presentation.pptx
satatistics Presentation.pptx
 
R m 99
R m 99R m 99
R m 99
 
Biostatistics and Research Methodology Semester 8
Biostatistics and Research Methodology Semester 8Biostatistics and Research Methodology Semester 8
Biostatistics and Research Methodology Semester 8
 
Chapter_1_Lecture.pptx
Chapter_1_Lecture.pptxChapter_1_Lecture.pptx
Chapter_1_Lecture.pptx
 
Multivariate Variate Techniques
Multivariate Variate TechniquesMultivariate Variate Techniques
Multivariate Variate Techniques
 
Selection of appropriate data analysis technique
Selection of appropriate data analysis techniqueSelection of appropriate data analysis technique
Selection of appropriate data analysis technique
 
Introduction to Statistics
Introduction to StatisticsIntroduction to Statistics
Introduction to Statistics
 
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptxBASIC STATISTICAL TREATMENT IN RESEARCH.pptx
BASIC STATISTICAL TREATMENT IN RESEARCH.pptx
 
tests of significance
tests of significancetests of significance
tests of significance
 

More from AthenaYshelleYsit

More from AthenaYshelleYsit (6)

PPT PROKARYOTES vs EUKARYOTES.pptx.pdf
PPT PROKARYOTES vs EUKARYOTES.pptx.pdfPPT PROKARYOTES vs EUKARYOTES.pptx.pdf
PPT PROKARYOTES vs EUKARYOTES.pptx.pdf
 
EL FILI 1-5.pptx
EL FILI 1-5.pptxEL FILI 1-5.pptx
EL FILI 1-5.pptx
 
NOLI ME TANGERE ACROSTIC
NOLI ME TANGERE ACROSTICNOLI ME TANGERE ACROSTIC
NOLI ME TANGERE ACROSTIC
 
Black-and-White-Basic-Presentation-Template-1 (1).pdf
Black-and-White-Basic-Presentation-Template-1 (1).pdfBlack-and-White-Basic-Presentation-Template-1 (1).pdf
Black-and-White-Basic-Presentation-Template-1 (1).pdf
 
statistics.ppt
statistics.pptstatistics.ppt
statistics.ppt
 
Lecture-1.ppt
Lecture-1.pptLecture-1.ppt
Lecture-1.ppt
 

Recently uploaded

100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptxAnupama Kate
 
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...amitlee9823
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Delhi Call girls
 
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779Best VIP Call Girls Noida Sector 39 Call Me: 8448380779
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779Delhi Call girls
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023ymrp368
 
April 2024 - Crypto Market Report's Analysis
April 2024 - Crypto Market Report's AnalysisApril 2024 - Crypto Market Report's Analysis
April 2024 - Crypto Market Report's Analysismanisha194592
 
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...amitlee9823
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAroojKhan71
 
Edukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxEdukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxolyaivanovalion
 
Discover Why Less is More in B2B Research
Discover Why Less is More in B2B ResearchDiscover Why Less is More in B2B Research
Discover Why Less is More in B2B Researchmichael115558
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...shivangimorya083
 
Carero dropshipping via API with DroFx.pptx
Carero dropshipping via API with DroFx.pptxCarero dropshipping via API with DroFx.pptx
Carero dropshipping via API with DroFx.pptxolyaivanovalion
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxolyaivanovalion
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfLars Albertsson
 
Ravak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxRavak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxolyaivanovalion
 
Accredited-Transport-Cooperatives-Jan-2021-Web.pdf
Accredited-Transport-Cooperatives-Jan-2021-Web.pdfAccredited-Transport-Cooperatives-Jan-2021-Web.pdf
Accredited-Transport-Cooperatives-Jan-2021-Web.pdfadriantubila
 

Recently uploaded (20)

100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx
 
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...
Call Girls Hsr Layout Just Call 👗 7737669865 👗 Top Class Call Girl Service Ba...
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
 
Abortion pills in Doha Qatar (+966572737505 ! Get Cytotec
Abortion pills in Doha Qatar (+966572737505 ! Get CytotecAbortion pills in Doha Qatar (+966572737505 ! Get Cytotec
Abortion pills in Doha Qatar (+966572737505 ! Get Cytotec
 
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779Best VIP Call Girls Noida Sector 39 Call Me: 8448380779
Best VIP Call Girls Noida Sector 39 Call Me: 8448380779
 
Sampling (random) method and Non random.ppt
Sampling (random) method and Non random.pptSampling (random) method and Non random.ppt
Sampling (random) method and Non random.ppt
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023
 
April 2024 - Crypto Market Report's Analysis
April 2024 - Crypto Market Report's AnalysisApril 2024 - Crypto Market Report's Analysis
April 2024 - Crypto Market Report's Analysis
 
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...
Junnasandra Call Girls: 🍓 7737669865 🍓 High Profile Model Escorts | Bangalore...
 
(NEHA) Call Girls Katra Call Now 8617697112 Katra Escorts 24x7
(NEHA) Call Girls Katra Call Now 8617697112 Katra Escorts 24x7(NEHA) Call Girls Katra Call Now 8617697112 Katra Escorts 24x7
(NEHA) Call Girls Katra Call Now 8617697112 Katra Escorts 24x7
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
 
Edukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFxEdukaciniai dropshipping via API with DroFx
Edukaciniai dropshipping via API with DroFx
 
Discover Why Less is More in B2B Research
Discover Why Less is More in B2B ResearchDiscover Why Less is More in B2B Research
Discover Why Less is More in B2B Research
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
 
Carero dropshipping via API with DroFx.pptx
Carero dropshipping via API with DroFx.pptxCarero dropshipping via API with DroFx.pptx
Carero dropshipping via API with DroFx.pptx
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptx
 
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts ServiceCall Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdf
 
Ravak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxRavak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptx
 
Accredited-Transport-Cooperatives-Jan-2021-Web.pdf
Accredited-Transport-Cooperatives-Jan-2021-Web.pdfAccredited-Transport-Cooperatives-Jan-2021-Web.pdf
Accredited-Transport-Cooperatives-Jan-2021-Web.pdf
 

chapter1.ppt

  • 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.
  • 5.
  • 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.
  • 12.
  • 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.
  • 15.
  • 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.
  • 18.
  • 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.
  • 23.
  • 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.