Choose two of the following three questions and post your answer:1. In your own words, what is a nonparametric test? What is a parametric test (Section 13-2)?2. In your own words, identify an advantage of using rank correlation instead of linear correlation (Section 13-6).3. In your own words, what is the difference between a nonparametric test and a distribution-free test (Section 13-7)?use your own words!!Replies:Andressa- 1. In your own words, what is a nonparametric test? What is a parametric test (Section 13-2)?The parametric test is the hypothesis test which provides generalisations for making statements about the mean of the parent population. A t-test based on Student’s t-statistic, which is often used in this regard. The t-statistic rests on the underlying assumption that there is the normal distribution of variable and the mean in known or assumed to be known. The population variance is calculated for the sample. It is assumed that the variables of interest, in the population are measured on an interval scale.The nonparametric test is defined as the hypothesis test which is not based on underlying assumptions, i.e. it does not require population’s distribution to be denoted by specific parameters. The test is mainly based on differences in medians. Hence, it is alternately known as the distribution-free test. The test assumes that the variables are measured on a nominal or ordinal level. It is used when the independent variables are non-metric.3. In your own words, what is the difference between a nonparametric test and a distribution-free test (Section 13-7)?Nonparametric Test: Those procedures that test hypotheses that tests hypotheses that are not statements about population parameters are classified as nonparametric.Distribution free procedure: Those procedures that make no assumption about the sampled population are called distribution free procedures.Greg- Rank correlation had an advantage over linear correlation in that it can be used when data is not normal, but it's either categorical or ordinal. Linear correlation only applies when the data is normal and follows a linear pattern. Rank correlation allows us to find the correlation for data that does not fit this. Parametric tests are used when we have assumptions about the distribution of the population that the data was taken from. An example of this would be t tests. In contrast, nonparametric tests are not based on such assumptions and the data can be from a population that is not normally distributed. The Wilcoxon test is a nonparametric test.