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In academics, there is no magic to make things easier and done; however, you are required to do all that’s needed to avoid pitfalls. As a student who is doing an assignment that requires you to do various tests on data, there is no guarantee of an easy way out. When doing the analysis of data, one thing to completely avoid is mistakes. This is because if data analysis is not free from errors, then, the results obtained will not be reliable. Considering the complexity that most data analysis tests come with, getting very accurate results may be challenging especially if you are not very conversant with tests being done as well as the tools involved. The process of data analysis is quite lengthy, which begins at the gathering of genuine information and concluding with the presentation of very accurate results in a correct manner. Test of independence applies when you have two different variables from a single population. The test is hypothetical and helps you to know if one categorical variable depends on another variable. Just like any other statistical tests, you have to be conversant with both null and alternative hypothesis. A null hypothesis is what you assume to be right until you get enough proof against it. You need to know how to do the test of independence if you are interested in knowing if two categorical variables are related. You must assume that the variables are associated until you have enough evidence to prove that they are not. On the hand, you need to know that the alternative hypothesis is the hypothesis that is used contrary to the null hypothesis. In an alternative explanation, the observations are taken to be the result of a real effect. The test usually makes use of a table to analyze data.
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