6Dec19 morning Q19 Multiple Choice Questions

Answer
Comment
Array

Option : C
Explanation :
Non-parametric chi-square test will be the most appropriate in this case. There are two types of statistical inference methods: parametric and nonparametric.
In Parametric method one defines the probability distribution of probability variables and makes inferences about the parameters of the distribution.
In cases in which the probability distribution cannot be defined, nonparametric methods are employed. Nonparametric tests are less powerful than parametric tests, so we don't use them when parametric tests are appropriate. But if the assumptions of parametric tests are violated, we use nonparametric tests. Nonparametric tests are classified according to the variables' level of measurement and the sample size. The chi-square test is used mainly when dealing with a nominal/categorical variable. The levels of the variable are discrete, mutually exclusive categories, and the data consist of frequencies or counts for each category.
T tests are a type of parametric method; they are used to compare the means of two groups when the samples satisfy the conditions of normality, equal variance, and independence.
T tests can be of two types: (i) The independent t-test, which is used when the two groups under comparison are independent of each other; and (ii) the paired/correlated t-test, which is used when the two groups under comparison are dependent on each other.
Mann Whitney U test is a popular nonparametric test to compare outcomes between two independent. It is used to test whether two samples are likely to derive from the same population (i.e., that the two populations have the same shape).