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Basic Stats in R

This section covers some basic aspects of statistical analysis which are very often encountered in the course of any student’s normal progression. Most of the time, it is about comparing two or more groups to define whether there exists a difference or an association while considering a specific parameter or variable. But it isn’t only about that. It is important to understand a few concepts about the data to analyse. What is your dataset made of? What do you expect? What do you want to know? How much or what do you already know about the data?

Linear regression

in Basic Stats in R / Regression Analysis

Polynomial regression

in Basic Stats in R / Regression Analysis

Polynomial regression – when to draw the line?

in Basic Stats in R / Regression Analysis

Which ANOVA – One-way? Two-way? Repeated measures?

in ANalysis Of VAriance (ANOVA) / Basic Stats in R

One-way ANOVA

in ANalysis Of VAriance (ANOVA) / Basic Stats in R

Factorial design (two-way ANOVA)

in ANalysis Of VAriance (ANOVA) / Basic Stats in R

Repeated Measures ANOVA

in ANalysis Of VAriance (ANOVA) / Basic Stats in R

Post-Hoc Tests

in Basic Stats in R / Post Hoc tests

Post Hoc Tests – Tukey HSD

in Basic Stats in R / Post Hoc tests

Factorial Repeated Measures ANOVA (Two-way repeated measures ANOVA)

in ANalysis Of VAriance (ANOVA) / Basic Stats in R

Post Hoc Tests – Pairwise Comparisons with corrections

in Basic Stats in R / Post Hoc tests

Post Hoc Tests – multiple comparisons in linear models

in Basic Stats in R / Post Hoc tests

Post Hoc Tests – multiple comparisons in linear mixed effect models

in Basic Stats in R / Post Hoc tests

Post Hoc Tests – multiple comparisons in linear mixed effect models [factorial design]

in Basic Stats in R / Post Hoc tests

Post Hoc Tests – multiple comparisons in linear models [factorial design]

in Basic Stats in R / Post Hoc tests

Friedman rank sum test

in Basic Stats in R / Useful tests

Test for normality – Shapiro-Wilk test

in Basic Stats in R / Useful tests

Test for homogeneity of variances – Levene’s test and the Fligner-Killeen test

in Basic Stats in R / Useful tests

Test for sphericity – Mauchly’s test

in Basic Stats in R / Useful tests

Finding outliers

in Basic Stats in R / Useful tests

1. Comparing two variances – Fisher’s F test

in Basic Stats in R / Two-sample analysis / Useful tests

2. Comparing two means – which test to choose?

in Basic Stats in R / Two-sample analysis

3. Comparing two proportions

in Basic Stats in R / Two-sample analysis

4. Comparing two variables

in Basic Stats in R / Two-sample analysis

Comparing two means – Student’s t-test

in Basic Stats in R / Two-sample analysis

Comparing two means – Mann-Whitney U test

in Basic Stats in R / Two-sample analysis

Comparing two means – Kruskal-Wallis test

in Basic Stats in R / Two-sample analysis

Comparing two means – Student’s paired t-test

in Basic Stats in R / Two-sample analysis

Comparing two means – Wilcoxon signed-rank test

in Basic Stats in R / Two-sample analysis

Comparing two means – one-tailed or two-tailed tests?

in Basic Stats in R / Two-sample analysis

Comparing two variables – Pearson’s product-moment correlation

in Basic Stats in R / Two-sample analysis

Comparing two variables – Spearman’s rank-order correlation

in Basic Stats in R / Two-sample analysis

Comparing two variables – Kendall rank correlation coefficient

in Basic Stats in R / Two-sample analysis

Comparing two variables – Chi-square test and Fisher’s exact test

in Basic Stats in R / Two-sample analysis

1. One-sample analysis? For what…?

in Basic Stats in R / One-sample analysis

2. Choose a one-sample test!

in Basic Stats in R / One-sample analysis

3. Run a one-sample t-test.

in Basic Stats in R / One-sample analysis

4. Run a one-sample z-test.

in Basic Stats in R / One-sample analysis

5. So, what about our example?

in Basic Stats in R / One-sample analysis

The following screenshot was taken from the datasheet bound to the package TeachingDemos. It reduces the problem of choice between z-test and t-test to “in real life, no one use z-test !”. Just so that you know…

6. “Fun” fact about z.test (according to TeachingDemos)

in Basic Stats in R / One-sample analysis

1. Mean

in Basic Stats in R / Descriptive Stats

2. Median

in Basic Stats in R / Descriptive Stats

3. Minimum, maximum and range

in Basic Stats in R / Descriptive Stats

4. Variance

in Basic Stats in R / Descriptive Stats

5. Standard Deviation

in Basic Stats in R / Descriptive Stats

6. Quartiles

in Basic Stats in R / Descriptive Stats

7. Boxplot

in Basic Stats in R / Descriptive Stats

8. Summary()

in Basic Stats in R / Descriptive Stats

9. Pastecs

in Basic Stats in R / Descriptive Stats