Lab manual QuantRMA
Preface
Important notes
Attributions
CC BY-SA 4.0 license
Getting started
0.1
Why R?
0.2
Downloading and installing R
0.2.1
Installing R on a Mac
0.2.2
Installing R on a Windows PC
0.2.3
Installing R on a Linux PC
0.3
Downloading and installing RStudio
0.4
Understanding RStudio
0.4.1
Console
0.4.2
Script Editor
0.4.3
Workspace and History
0.4.4
File, Plot, Packages, Help
0.4.5
Installing libraries
0.5
How to complete the labs
0.5.1
R project
0.5.2
RMarkdown
1
Week 1: Introduction
1.1
Learning goals
1.2
How to use this lab manual
1.3
RMarkdown basics
1.4
Research methods: measurement
1.4.1
Question 1
1.4.2
Question 2
1.4.3
Question 3
1.4.4
Question 4
1.4.5
Question 5
1.4.6
Question 6
1.4.7
Question 7
1.5
Basic R
1.5.1
Doing simple calculations with R
1.5.2
Using functions to do calculations
1.5.3
Storing a number as a variable
1.5.4
Using comments
1.5.5
R is pretty stupid?
2
Week 2: Describing Data
2.1
Learning goals
2.2
Loading data
2.2.1
First look at the data
2.3
Making graphs
2.3.1
Wrangle first
2.3.2
Plotting
counts
2.3.3
Additional materials:
ggplot()
layers and functions
2.4
Gapminder dataset
2.4.1
Look at the data
2.4.2
Life expectancy
2.5
Using numbers to describe data
2.5.1
Playing with numbers
2.5.2
Central Tendency
2.5.3
Variation
2.5.4
Descriptives by conditions
2.5.5
Describing Gapminder with numbers
3
Week 3: Correlation and Causation
3.1
Learning goals
3.2
Research methods: causality
3.2.1
Question 1
3.2.2
Question 2
3.2.3
Question 3
3.2.4
Question 4
3.2.5
Question 5
3.2.6
Question 6
3.2.7
Question 7
3.2.8
Question 8
3.3
Correlations in R
3.3.1
cor()
for correlation
3.3.2
Correlation exercises
3.4
Real data
3.4.1
Load the data
3.4.2
Look at the data
3.4.3
Example question #1
3.4.4
Example question #2
3.4.5
Theory exercises
3.4.6
Data exercise
4
Week 4: Chance and Probability Theory
4.1
Learning goals
4.2
Correlation and random chance
4.2.1
Chance exercises
4.3
Generating data with
sample()
and
binom()
4.3.1
sample()
4.3.2
rbinom()
4.3.3
sample
and
binom()
exercises
4.4
Normal distribution
4.4.1
rnorm()
4.4.2
Graphing the normal distribution
4.4.3
Calculating the probability of specific ranges.
4.4.4
norm()
exercises
4.5
z-scores
4.5.1
z-score exercises
5
Week 5: Estimation and Sampling Theory
5.1
Learning goals
5.2
Collecting some data
5.3
Statistical theory: sampling and estimation
5.3.1
Question 1
5.3.2
Question 2
5.3.3
Question 3
5.3.4
Question 4
5.3.5
Question 5
5.3.6
Question 6
5.3.7
Question 7
5.3.8
Question 8
5.3.9
Question 9
5.4
Stroop data
5.4.1
Stroop data exercises
6
Week 6: Hypothesis Testing
6.1
Learning goals
6.2
Statistical theory: hypothesis testing
6.2.1
Question 1
6.2.2
Question 2
6.2.3
Question 3
6.2.4
Question 4
6.2.5
Question 5
6.2.6
Question 6
6.2.7
Question 7
6.2.8
Question 8
6.2.9
Question 9
6.3
\(t\)
-tests in R
6.4
Stroop data
6.4.1
\(t\)
-test exercises
7
Function list
7.1
Week 1
7.2
Week 2
7.3
Week 3
7.4
Week 4
7.5
Week 5
7.6
Week 6
8
References
Published with bookdown
Lab manual QuantRMA
8
References
R Core Team. 2020.
R: A Language and Environment for Statistical Computing
. Vienna, Austria: R Foundation for Statistical Computing.
https://www.R-project.org/
.