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 (Kanji 2006).)
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.
|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).