Chi-Square test of analysis is usually used to determine the independence or association of categorical variables that arise from simple random sampling (McDonald, 2009).

Categorical variables are qualitative and are three types; nominal, ordinal and dichotomous variables and all these kinds can be used in chi- square test.

A nominal variable is simply a name category, for example, the sex of respondents (male or female) and the diseases they possess (such as malaria and cholera). Ordinal variable, on the other hand, is made of a set of observations that have a direction or order, for example, highlighting the number of respondents who were severely ill, mildly ill and not ill.

The one-sample t-test is used for measured variables, by comparing the mean of these two variables (Norman, & Streiner, 2014). It is used to determine whether the sample that has been used has come from a given population by comparing the mean of the sample to a particular population mean. One-sample t-test has some assumptions that need adherences to and informs the type of variables to be used that include both interval and ratio variables.

Interval variables are ones that can be measured quantitatively, for example, the time it has taken for one to recover fully after consuming a new drug such as six hours.

Ratio variables also used in One-sample t- test assigns real numbers to observations at equal intervals that can be measured and has an absolute zero point for example age of respondents.

Paired t-test is used to determine whether the mean of a dependent variable such as temperature is the same in two related groups showing two time periods. The dependent variable can be measured to be an interval or ratio variable, and the independent variable can be nominal or ordinal variable with two categories.