Statistics Lab Manual
Preface
0.1
Important notes
0.1.1
Attributions
0.1.2
CC BY-SA 4.0 license
0.1.3
Copying the lab manual
0.1.4
Acknowledgments
Software
0.2
Data
0.2.1
Data Repository
0.2.2
CSV format
0.2.3
SPSS format
0.3
R
0.3.1
Why R?
0.3.2
Installing R and R Studio
0.3.3
R studio notes and tips
0.3.4
How to complete the R Labs
0.3.5
Screencast tutorial
0.3.6
R-studio Cloud
0.4
Excel
0.5
SPSS
0.6
JAMOVI
1
Lab 1: Graphing Data
1.1
General Goals
1.1.1
Important info
1.2
Excel
1.2.1
Goals
1.2.2
Load the data
1.2.3
Inspect the data
1.2.4
Preparing the data
1.2.5
Bar graph by borough
1.2.6
Bar graph by type, Brooklyn only
1.2.7
Histogram of permit duration
1.2.8
Reporting and interpreting our results
1.2.9
On Your Own
2
Lab 2: Descriptive Statistics
2.1
General Goals
2.1.1
Important info
2.2
Excel
2.2.1
Statistics Covered
2.2.2
Load the data
2.2.3
Sort and Split
2.2.4
Calculate Descriptive statistics
2.2.5
Interpert our results
2.2.6
Conditional Function Method
2.2.7
On Your Own
3
Lab 3: Correlation
3.1
General Goals
3.1.1
Important Info
3.2
Excel
3.2.1
Goals
3.2.2
Load the data
3.2.3
Removing unnecessary worksheets
3.2.4
Calculate Pearson’s r, and the coefficient of determination
3.2.5
Generate a scatter plot
3.2.6
Interpreting our results
3.2.7
On Your Own
4
Lab 4: Normal Distribution & Central Limit Theorem
4.1
General Goals
4.2
Excel
4.2.1
Goals
4.2.2
Load the data
4.2.3
Calculate descriptive statistics
4.2.4
Calculate Z score of x-value
4.2.5
Calculate percentage of the normal curve above and below X
4.2.6
Reverse Z score calculator
4.2.7
On Your Own
5
Lab 5: Fundamentals of Hypothesis Testing
5.1
Overview
5.2
Excel
5.2.1
Goals
5.2.2
Load the data
5.2.3
Calculate difference scores between pairs of measures
5.2.4
State the hypotheses
5.2.5
Determine the observed value
5.2.6
Calculate the 2-tailed significance
5.2.7
Reporting and Interpreting your result
5.2.8
Calculating a sign test without difference scores
5.2.9
On Your Own
6
Lab 6: t-Test (one-sample, paired sample)
6.1
Does Music Convey Social Information to Infants?
6.1.1
STUDY DESCRIPTION
6.2
Lab skills learned
6.3
Important Stuff
6.4
R
6.4.1
Loading the data
6.4.2
Inspect the data frame
6.4.3
Get the data for Experiment one
6.4.4
Baseline phase: Conduct a one sample t-test
6.4.5
Test phase
6.4.6
Paired-samples t-test
6.4.7
Graphing the findings
6.4.8
Data-simulation
6.4.9
Generalization Exercise
6.4.10
Writing assignment
6.5
Excel
6.6
SPSS
6.6.1
Experiment Background
6.6.2
Performing a one-sample t-test
6.6.3
Performing a paired-samples t-test
6.6.4
Graphing your results
6.6.5
The relationship between the one-sample and the paired-samples t-test
6.6.6
Practice Problems
6.7
JAMOVI
7
Lab 7: t-test (Independent Sample)
7.1
Do you come across as smarter when people read what you say or hear what you say?
7.1.1
STUDY DESCRIPTION
7.2
Lab skills learned
7.3
Important Stuff
7.4
R
7.4.1
Load the data
7.4.2
Inspect data frame
7.4.3
Find the data you need
7.4.4
Look at the dependent variable.
7.4.5
Conduct Independent samples t-test
7.4.6
Remaining ratings
7.4.7
Reconstructing the graph from the paper
7.4.8
Generalization Exercise
7.4.9
Writing assignment
7.5
Excel
7.6
SPSS
7.6.1
Experiment Background
7.6.2
Performing an independent-samples t-test
7.6.3
Graphing your data
7.6.4
Practice Problems
7.7
JAMOVI
8
Lab 8 One-way ANOVA
8.1
How to not think about bad memories by playing Tetris
8.1.1
STUDY DESCRIPTION
8.1.2
Study Methods
8.2
Lab Skills Learned
8.3
Important Stuff
8.4
R
8.4.1
Load the data
8.4.2
Inspect the dataframe
8.4.3
Get the data you need
8.4.4
Look at the data
8.4.5
Conduct the ANOVA
8.4.6
Reporting the ANOVA results
8.4.7
Individual comparisons
8.4.8
Writing it all up.
8.4.9
Food for thought
8.4.10
Generalization Exercise
8.4.11
Writing assignment
8.5
Excel
8.6
SPSS
8.6.1
Experiment Background
8.6.2
Performing a One-Factor Analysis of Variance (ANOVA) & Graphing the data
8.6.3
Planned Comparisons: T-tests
8.6.4
Unplanned Comparisons: Post-hoc tests
8.6.5
Practice Problems
8.7
JAMOVI
9
Lab 9 Repeated Measures ANOVA
9.1
Betcha can’t type JHDBZKCO very fast on your first try
9.1.1
STUDY DESCRIPTION
9.1.2
Study Methods
9.2
Lab Skills Learned
9.3
Important Stuff
9.4
R
9.4.1
Load the data
9.4.2
Inspect the dataframe
9.4.3
Get the data you need
9.4.4
Look at the data
9.4.5
Look at the means
9.4.6
Conduct the repeated Measures ANOVA
9.4.7
Follow-up comparisons
9.4.8
Reporting everything
9.4.9
Generalization Exercise
9.4.10
Writing assignment
9.5
Excel
9.6
SPSS
9.6.1
Experiment Background
9.6.2
Produce a frequency histogram and remove outliers
9.6.3
Conduct and graph One-Factor Repeated Measures ANOVA
9.6.4
Conduct planned comparisons using a paired-samples t-test
9.6.5
Practice Problems
9.7
JAMOVI
10
Lab 10: Factorial ANOVA
10.1
Does standing up make you focus more?
10.1.1
STUDY DESCRIPTION
10.1.2
Study Methods
10.2
Lab Skills Learned
10.3
Important Stuff
10.4
R
10.4.1
Load the data
10.4.2
Inspect the dataframe
10.4.3
Get the data you need
10.4.4
Get the data into the format you want
10.4.5
Look at the data
10.4.6
Look at the means
10.4.7
Conduct the ANOVA
10.4.8
Between Subjects ANOVA
10.4.9
Repeated measures ANOVA
10.4.10
Follow-up comparisons
10.4.11
Generalization Exercise
10.4.12
Writing asignment
10.5
Excel
10.6
SPSS
10.6.1
Experiment Background
10.6.2
Conduct a Between-Subjects Two-Factor Analysis of Variance (ANOVA)
10.6.3
Calculate simple effects
10.6.4
Conduct a Repeated Measures Two-Factor Analysis of Variance (ANOVA)
10.6.5
Calculate simple effects
10.6.6
Practice Problems
10.7
JAMOVI
11
Lab 11: Mixed Factorial ANOVA
11.1
Do you remember things better when you take pictures of them?
11.1.1
Study description
11.2
Lab Skills Learned
11.3
Important Stuff
11.4
R
11.4.1
Load the data
11.4.2
Inspect the dataframe
11.4.3
Get the data you need
11.4.4
Get the data into the format you want
11.4.5
Look at the data
11.4.6
Look at the means
11.4.7
Conduct the ANOVA
11.4.8
Generalization Exercise
11.4.9
Writing assignment
11.5
Excel
11.6
SPSS
11.6.1
Experiment Background
11.6.2
Conduct a Mixed-Factorial Analysis of Variance (ANOVA)
11.6.3
Calculate simple effects
11.6.4
Practice Problems
11.7
JAMOVI
Preface
11.8
Important notes
11.8.1
Attributions
11.8.2
CC BY-SA 4.0 license
11.8.3
Copying the lab manual
11.8.4
Acknowledgments
11.9
Data
11.9.1
Data Repository
11.9.2
CSV format
11.9.3
SPSS format
11.10
R
11.10.1
Why R?
11.10.2
Installing R and R Studio
11.10.3
R studio notes and tips
11.10.4
How to complete the R Labs
11.10.5
Screencast tutorial
11.10.6
R-studio Cloud
11.11
Excel
11.12
SPSS
11.13
JAMOVI
12
Lab 1: Graphing Data
12.1
General Goals
12.1.1
Important info
12.2
R
12.2.1
Download the lab templates
12.2.2
Get some data
12.2.3
Look at the data
12.2.4
Make Plots to answer questions
12.2.5
ggplot2 basics
12.2.6
More questions about NYC films
12.2.7
Gapminder Data
12.2.8
Asking Questions with the gap minder data
12.2.9
Generalization Exercise
12.2.10
Writing assignment
12.3
Excel
12.3.1
Goals
12.3.2
Load the data
12.3.3
Inspect the data
12.3.4
Preparing the data
12.3.5
Bar graph by borough
12.3.6
Bar graph by type, Brooklyn only
12.3.7
Histogram of permit duration
12.3.8
Reporting and interpreting our results
12.3.9
On Your Own
12.4
SPSS
12.4.1
Opening SPSS and the SPSS layout
12.4.2
Reviewing variable properties and the Variable View tab
12.4.3
Opening a data file and producing different types of graphs
12.4.4
Practice Problems
12.5
JAMOVI
13
Lab 2: Descriptive Statistics
13.1
General Goals
13.1.1
Important info
13.2
R
13.2.1
Descriptives basics in R
13.2.2
Central Tendency
13.2.3
Variation
13.2.4
Descriptives by conditions
13.2.5
Describing gapminder
13.2.6
Generalization Exercise
13.2.7
Writing assignment
13.3
Excel
13.4
SPSS
13.4.1
Calculating Descriptive Statistics
13.4.2
Descriptive Statistics and Histograms
13.4.3
Editing graphs
13.4.4
Practice Problems
13.5
JAMOVI
14
Lab 3: Correlation
14.1
General Goals
14.1.1
Important Info
14.2
R
14.2.1
cor for correlation
14.2.2
World Happiness Report
14.2.3
Generalization Exercise
14.2.4
Writing assignment
14.3
Excel
14.4
SPSS
14.4.1
Correlation Coefficient for Bivariate Data: Two Variables
14.4.2
Correlation Matrix
14.4.3
Correlation and Scatterplots
14.4.4
Splitting a File
14.4.5
Practice Problems
14.5
JAMOVI
15
Lab 4: Normal Distribution & Central Limit Theorem
15.1
General Goals
15.2
R
15.2.1
Generating Numbers in R
15.2.2
sampling distribution of the mean.
15.2.3
Sampling distributions for any statistic
15.2.4
Central limit theorem
15.2.5
The normal distribution
15.2.6
z-scores
15.2.7
Generalization Exercise
15.2.8
Writing assignment
15.3
Excel
15.4
SPSS
15.4.1
Saving data as standardized values.
15.4.2
Computing variables
15.4.3
Practice Problems
15.5
JAMOVI
16
Lab 5: Fundamentals of Hypothesis Testing
16.1
R
16.1.1
The Crump Test
16.1.2
Crumping real data
16.1.3
The Randomization Test
16.1.4
Generalization Exercise
16.1.5
Writing assignment
16.2
Excel
16.3
SPSS
16.3.1
Experiment Background
16.3.2
Calculate difference scores between pairs of measures
16.3.3
Conduct a sign test
16.3.4
Entering data for sign test problems
16.3.5
Practice Problems
16.4
JAMOVI
17
Lab 6: t-Test (one-sample, paired sample)
17.1
Does Music Convey Social Information to Infants?
17.1.1
STUDY DESCRIPTION
17.2
Lab skills learned
17.3
Important Stuff
17.4
R
17.4.1
Loading the data
17.4.2
Inspect the data frame
17.4.3
Get the data for Experiment one
17.4.4
Baseline phase: Conduct a one sample t-test
17.4.5
Test phase
17.4.6
Paired-samples t-test
17.4.7
Graphing the findings
17.4.8
Data-simulation
17.4.9
Generalization Exercise
17.4.10
Writing assignment
17.5
Excel
17.6
SPSS
17.6.1
Experiment Background
17.6.2
Performing a one-sample t-test
17.6.3
Performing a paired-samples t-test
17.6.4
Graphing your results
17.6.5
The relationship between the one-sample and the paired-samples t-test
17.6.6
Practice Problems
17.7
JAMOVI
18
Lab 7: t-test (Independent Sample)
18.1
Do you come across as smarter when people read what you say or hear what you say?
18.1.1
STUDY DESCRIPTION
18.2
Lab skills learned
18.3
Important Stuff
18.4
R
18.4.1
Load the data
18.4.2
Inspect data frame
18.4.3
Find the data you need
18.4.4
Look at the dependent variable.
18.4.5
Conduct Independent samples t-test
18.4.6
Remaining ratings
18.4.7
Reconstructing the graph from the paper
18.4.8
Generalization Exercise
18.4.9
Writing assignment
18.5
Excel
18.6
SPSS
18.6.1
Experiment Background
18.6.2
Performing an independent-samples t-test
18.6.3
Graphing your data
18.6.4
Practice Problems
18.7
JAMOVI
19
Lab 8 One-way ANOVA
19.1
How to not think about bad memories by playing Tetris
19.1.1
STUDY DESCRIPTION
19.1.2
Study Methods
19.2
Lab Skills Learned
19.3
Important Stuff
19.4
R
19.4.1
Load the data
19.4.2
Inspect the dataframe
19.4.3
Get the data you need
19.4.4
Look at the data
19.4.5
Conduct the ANOVA
19.4.6
Reporting the ANOVA results
19.4.7
Individual comparisons
19.4.8
Writing it all up.
19.4.9
Food for thought
19.5
control vs reactivation+Tetris
19.6
Tetris_only vs reactivation+Tetris
19.6.1
Generalization Exercise
19.6.2
Writing assignment
19.7
Excel
19.8
SPSS
19.8.1
Experiment Background
19.8.2
Performing a One-Factor Analysis of Variance (ANOVA) & Graphing the data
19.8.3
Planned Comparisons: T-tests
19.8.4
Unplanned Comparisons: Post-hoc tests
19.8.5
Practice Problems
19.9
JAMOVI
20
Lab 9 Repeated Measures ANOVA
20.1
Betcha can’t type JHDBZKCO very fast on your first try
20.1.1
STUDY DESCRIPTION
20.1.2
Study Methods
20.2
Lab Skills Learned
20.3
Important Stuff
20.4
R
20.4.1
Load the data
20.4.2
Inspect the dataframe
20.4.3
Get the data you need
20.4.4
Look at the data
20.4.5
Look at the means
20.5
get subject mean RTs
20.6
get condition mean RTs
20.7
plot the condition means
20.8
get subject mean RTs
20.9
get condition mean RTs
20.10
plot the condition means
20.10.1
Conduct the repeated Measures ANOVA
20.11
get subject mean RTs
20.12
get condition mean RTs
20.12.1
Follow-up comparisons
20.12.2
Reporting everything
20.12.3
Generalization Exercise
20.12.4
Writing assignment
20.13
Excel
20.14
SPSS
20.14.1
Experiment Background
20.14.2
Produce a frequency histogram and remove outliers
20.14.3
Conduct and graph One-Factor Repeated Measures ANOVA
20.14.4
Conduct planned comparisons using a paired-samples t-test
20.14.5
Practice Problems
20.15
JAMOVI
21
Lab 10: Factorial ANOVA
21.1
Does standing up make you focus more?
21.1.1
STUDY DESCRIPTION
21.1.2
Study Methods
21.2
Lab Skills Learned
21.3
Important Stuff
21.4
R
21.4.1
Load the data
21.4.2
Inspect the dataframe
21.4.3
Get the data you need
21.4.4
Get the data into the format you want
21.4.5
Look at the data
21.4.6
Look at the means
21.4.7
Conduct the ANOVA
21.4.8
Between Subjects ANOVA
21.4.9
Repeated measures ANOVA
21.4.10
Follow-up comparisons
21.4.11
Generalization Exercise
21.4.12
Writing asignment
21.5
Excel
21.6
SPSS
21.6.1
Experiment Background
21.6.2
Conduct a Between-Subjects Two-Factor Analysis of Variance (ANOVA)
21.6.3
Calculate simple effects
21.6.4
Conduct a Repeated Measures Two-Factor Analysis of Variance (ANOVA)
21.6.5
Calculate simple effects
21.6.6
Practice Problems
21.7
JAMOVI
22
Lab 11: Mixed Factorial ANOVA
22.1
Do you remember things better when you take pictures of them?
22.1.1
Study description
22.2
Lab Skills Learned
22.3
Important Stuff
22.4
R
22.4.1
Load the data
22.4.2
Inspect the dataframe
22.4.3
Get the data you need
22.4.4
Get the data into the format you want
22.4.5
Look at the data
22.4.6
Look at the means
22.4.7
Conduct the ANOVA
22.4.8
Generalization Exercise
22.4.9
Writing assignment
22.5
Excel
22.6
SPSS
22.6.1
Experiment Background
22.6.2
Conduct a Mixed-Factorial Analysis of Variance (ANOVA)
22.6.3
Calculate simple effects
22.6.4
Practice Problems
22.7
JAMOVI
Published with bookdown
Answering questions with data: Lab Manual
Chapter 20
Lab 9 Repeated Measures ANOVA
Placeholder
20.1
Betcha can’t type JHDBZKCO very fast on your first try
20.1.1
STUDY DESCRIPTION
20.1.2
Study Methods
20.2
Lab Skills Learned
20.3
Important Stuff
20.4
R
20.4.1
Load the data
20.4.2
Inspect the dataframe
20.4.3
Get the data you need
20.4.3.1
The independent variable
20.4.3.2
The dependent variables
20.4.4
Look at the data
20.4.5
Look at the means
20.5
get subject mean RTs
20.6
get condition mean RTs
20.7
plot the condition means
20.8
get subject mean RTs
20.9
get condition mean RTs
20.10
plot the condition means
20.10.1
Conduct the repeated Measures ANOVA
20.10.1.1
Report the means too
20.11
get subject mean RTs
20.12
get condition mean RTs
20.12.1
Follow-up comparisons
20.12.1.1
Normal vs Bigrams
20.12.1.2
Bigrams vs Random
20.12.2
Reporting everything
20.12.2.1
First way
20.12.2.2
Second way
20.12.3
Generalization Exercise
20.12.4
Writing assignment
20.13
Excel
20.14
SPSS
20.14.1
Experiment Background
20.14.2
Produce a frequency histogram and remove outliers
20.14.3
Conduct and graph One-Factor Repeated Measures ANOVA
20.14.4
Conduct planned comparisons using a paired-samples t-test
20.14.5
Practice Problems
20.15
JAMOVI
