The majority of the time we deal with continous data that are normally distributed. What about data that are not continuous and/or normally distributed? How would we test for differences or analyze relationships in this case? 1. Describe, through an example, a variable that is not continuous in nature. 2. Describe a nonparametric test other than chi-square and what it is used for. NOTE: Please do not answer by cutting and pasting the response from other sites.

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The majority of the time we deal with continous data that are normally distributed. What about data that are not continuous and/or normally distributed? How would we test for differences or analyze relationships in this case?    1.  Describe, through an example, a variable that is not continuous in nature.   2.  Describe a nonparametric test other than chi-square and what it is used for.     NOTE:  Please do not answer by cutting and pasting the response from other sites.

Velsenw · Accepted Answer

Step 1A non-parametric test is used when the data is not normally distributed (or not a continuous and very small sample size).To test for differences or analyze relationships, in this case, there is the following non-parametric test:The given data set is:TestThe test is used for1-sample sign testTo test for a median estimate1-sample Wilcoxon signed-rank testCompare the medianFriedman testDifference between groupsGoodman Kruskal&#039;s GammaA test of association for two ranked variablesKruskal-Wallis testOne-way ANOVA non-parametricMann-Whitney testTest for two independent sampleSpearman-Rank CorrelationA correlation test between two sets of dataStep 21) A variable is said to be continuous in nature that can take an infinite number of values between two integer values.For example:1. A Binary number is not a continuous variable because it takes only 0 and 1.2. A rank of marks in a class of students is not a continuous variable.Step 32) A non-parametric test is used to compare the median for two different populations.A part of the chi-square, the Mann-Whitney u test is also a non-parametric test.A Mann-Whitney u test is used to test whether the two populations are different or not.For example,In an experiment, we want to test the effectiveness of a new drug. Therefore, the total number of participants is 10.Here, to test the effect of a new drug, a Mann-Whitney u test would be appropriate.

The majority of the time we deal with continous data that are normally distribut

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