Practice Problems/Analyses: ANSWERS IN RED
1. Recode the Treatment Satisfaction variable into the following levels and name
your new variable KH_TreatSat_Groups (using your initials).
a. 1 = Low Satisfaction (0 - 33)
b. 2 = Moderate Satisfaction (34 - 65)
Question 1 of 20
1.0 Points
Which of the following research situations would be most likely to use a between-subjects research
design?
A. Examining academic performance of the Texas State University students by comparing
their mean GPA to the national ave
PSY 2301 Lecture 12
Analysis of Variance
Yueqin Jean Hu
Teaching Goal
To introduce the logical foundation for analysis of variance
(ANOVA)
To demonstrate the process of hypothesis testing with ANOVA
To demonstrate the use of post tests to help interpre
2101 Introduction to Statistics Lab 10
Correlations
A Correlation is used when evaluating the strength of the relationship between two variables.
These variables are measured on ordinal or interval/ratio scales (not nominal).
A Pearson Correlation is used
2101 Introduction to Statistics Lab 9
Factorial ANOVA
Like the One-Way ANOVA, Factorial ANOVA tests mean differences between groups and the
Dependent Variable is measured on an Interval/Ratio scale. However, instead of a single
Independent Variable, Facto
2101 Introduction to Statistics Lab 6
One-Sample and Independent t-tests
Overview of t-tests: The t-tests are used when comparing the means of two groups. There are
three different types of t-tests: one-sample, independent and paired. Lab 6 covers one-sam
2101 Introduction to Statistics Lab 7
New: Paired t-Tests
Practice: One-Sample, Independent and Paired t-Tests
Paired t-tests (AKA: Dependent t-tests, Repeated-Sample t-tests, and Matched t-tests)
Paired t-tests are typically used when comparing the same
2101 Introduction to Statistics Lab 5
Compute Function and Recode Function
Transformations: Creating new variables based on other variables
Compute Variable (Transform -> Compute Variable)
In Survey Research, we will ask participants a series of questions
2101 Introduction to Statistics Lab 3
Measures of Central Tendency
Measures of Variation
Open the SPSS Lab 3 data set.
Part I: Central Tendency
Review: Central Tendency is a single value that best describes the center of the data set. There
are 3 Measures
PSY 2301 Lecture 14
Two-Factor Analysis of Variance
Yueqin Jean Hu
Teaching Goal
To introduce the concept of a two-factor
research design.
To introduce the concepts of main effects
and interactions
To demonstrate the process of hypothesis
testing with the
PSY 2301 Lecture 13
Repeated-Measures Analysis of Variance
Yueqin Jean Hu
Teaching Goal
To introduce the logic underlying the
repeated-measures analysis of variance.
To demonstrate the similarities and
differences between a repeated-measures
ANOVA and a
PSY 2301 Lecture 11
Paired Sample t Test
Yueqin Jean Hu
Teaching Goal
To introduce the basic characteristics of a
repeated-measures (or within-subjects)
research design
To demonstrate the process of hypothesis
testing with the repeated-measures t
To intro
PSY 2301 Lecture 10
Independent t Test
Yueqin Jean Hu
Teaching Goal
To introduce the basic characteristics of an
independent-measures (or between-subjects)
research design.
To demonstrate the process of hypothesis testing
with the independent-measures t
PSY 2301 Lecture 9
Introduction to the t Statistic
Yueqin Jean Hu
Teaching Goal
To introduce the t statistic as an
alternative to the z-score hypothesis test.
To demonstrate the calculation of
estimated standard error and the t
statistic
To introduce the
PSY 2301 Lecture 8
Hypothesis Testing
Yueqin Jean Hu
Teaching Goal
To introduce the statistic technique of hypothesis testing.
To introduce the concepts of null hypothesis, alpha level, and
critical region.
To introduce the types of errors that can occ
PSY 2301 Lecture 7
The Distribution of Sample Means
Yueqin Jean Hu
Teaching Goal
To introduce the distribution of sample
means and identify its parameters.
To demonstrate how z-scores can b used
to identify the location of a specific
sample mean within th
PSY 2301 Lecture 6
Probability
Yueqin Jean Hu
Teaching Goal
To introduce the concept of probability
To demonstrate how the unit normal table can be used to find
probabilities for any specific score, and how the table can be used
to find the score corres
PSY 2301 Lecture 5
z-Scores
Yueqin Jean Hu
Teaching Goal
To introduce z-scores as a method for
describing exact locations in a distribution
To demonstrate how raw scores (X
values) are transformed into z-scores,
and how to reverse the transformation
To de
PSY 2301 Lecture 4
Variability
Yueqin Jean Hu
Teaching Goal
To introduce the concept of variability and to describe
its importance as a descriptive measure and as a
component of inferential statistics.
To introduce the basic techniques for measuring and
Choosing Statistical Tests
Univariate Tests
Correlation Both the IV and DV are Continuous
One-Sample t-Test IV = Sample/General Population; DV = Continuous
Paired t-Test IV = Same Sample at 2 Time Points; DV = Continuous
Independent t Test IV = Nominal 2
2101 Introduction to Statistics Lab 2
Frequency Distributions
Bar Graphs and Histograms
Open the Lab 2 SPSS dataset.
Frequency Tables
1. To create a Frequency Table, you will click on the following sequence:
Analyze-> Descriptive Statistics-> Frequencies.
PSY 2301: Final Exam
The final exam will consist of approximately 75 multiple-choice questions (approximately 50
questions related to the last portion of the course material: Correlation & regression and Chi 2
tests, and 25 review questions).
The question
Introduction to Analysis of Variance
Analysis of Variance
Used to evaluate mean differences between more than two groups
t-test for independent samples can be used only to compare mean
differences between 2 groups
There are many different ANOVAs for di
Two-Factor ANOVA for independent groups
In one-factor ANOVA groups correspond to different levels of one
independent variable
In two-factor ANOVA effects of two independent variables are tested
In the simplest version 2 independent variables, each with
Correlation
Correlation measures and describes a
relationship between two variables, X & Y
Characteristics of X & Y relationships:
direction (negative or positive)
form (linear is most common)
strength
A Scatter plot of correlation
Direction of corre
Correlation
Correlation measures and describes a
relationship between two variables, X & Y
Characteristics of X & Y relationships:
direction (negative or positive)
form (linear is most common)
strength
A Scatter plot of correlation
Direction of corre
Introduction to Analysis of Variance
Analysis of Variance
Used to evaluate mean differences between more than two groups
t-test for independent samples can be used only to compare mean
differences between 2 groups
There are many different ANOVAs for di
The t ttest for aasingle sample:
The test for single sample:
an alternative to z-test
an alternative to z-test
Z-test reminder:
Compares a sample mean (M) after a treatment to the
population mean ()
Standard error describes how much difference is reason
Hypothesis Testing
Hypothesis Testing
A population has a mean = 80 and a standard deviation = 20.
What is the probability of randomly selecting a sample of n = 25 with a
sample mean of M = 84 or greater?
What is the probability of randomly selecting a sam
Two-Factor ANOVA for independent groups
In one-factor ANOVA groups correspond to different levels of one
independent variable
In two-factor ANOVA effects of two independent variables are tested
In the simplest version 2 independent variables, each with
Statistics- statistical procedures
Uses of statistics
-organize and summarize info
-determine exactly what conclusions are justified based on the results that were obtained
Goals of statistics
-accurate and meaningful interpretation
-Provide standardize e
Chapter 5
z-Scores: Location of Scores and
Standardized Distributions
PowerPoint Lecture Slides
Essentials of Statistics for the
Behavioral
Sciences
Eighth Edition
by Frederick J. Gravetter and Larry B. Wallnau
Chapter 5 Learning Outcomes
Tools You Will N
Chapter 10
The t Test for Two
Independent Samples
PowerPoint Lecture Slides
Essentials of Statistics for the
Behavioral
Sciences
Eighth Edition
by Frederick J Gravetter and Larry B. Wallnau
Chapter 10 Learning Outcomes
Tools You Will Need
Sample variance
Chapter 4
Measures of Variability
PowerPoint Lecture Slides
Essentials of Statistics for the
Behavioral Sciences
Eighth Edition
by Frederick J Gravetter and Larry B. Wallnau
Learning Outcomes
Tools You Will Need
Summation notation (Chapter 1)
Central te
Chapter 3
Measures of Central Tendency
PowerPoint Lecture Slides
Essentials of Statistics for the
Behavioral
Sciences
Eighth Edition
by Frederick J Gravetter and Larry B. Wallnau
Learning Outcomes
Tools You Will Need
Summation notation (Chapter 1)
Frequ