# 32 Selecting a hypothesis testing

Selecting the correct hypothesis test (or confidence interval) can be tricky… and in this book only a small number of hypothesis tests were described. (Literally hundreds of tests exist .)

For the tests studied in this book, determining if the response and explanatory variables are qualitative or quantitative is important (Table 32.1). So far, only situations with a qualitative explanatory variable have been considered. In the next chapters, cases where both the response and explanatory variables are quantitative are studied.

TABLE 32.1: Four different scenarios studied so far
Graphical summary Numerical summary Hypothesis test Confidence interval
Mean of one sample
Histogram; stem-and-leaf plot; dot chart Means, medians; Std. dev., IQR; etc. One-sample $$t$$ CI for one mean
Mean of differences (paired data)
Histogram of differences; case-profile Mean, std. dev. etc. of differences $$t$$-test for mean differences CI for mean difference
Comparing odds/percentages in two groups
Error bar chart Mean and std. error of the difference; mean, std. dev. etc. of each group $$t$$-test comparing the difference between two means CI of the difference between means
Comparing means in two groups
Side-by-side bar chart; stacked bar chart Odds; OR; percentages Chi-square test CI for OR

The following short video may help explain some of these concepts. Note that the test for correlation and regression have not yet been covered in this book (but they will be in the next few chapters).

### References

Kanji GK. 100 statistical tests. Sage; 2006.