300, replace = TRUE), sampleB = sample(c("Positive","Positive","Negative"), 300, replace = TRUE)) Perform the chi-square test using the chisq.test function: test <- chisq.test(x = data$sampleA, y = data$sampleB) Analyse the result: > test ...
A very small chi square test statistic means that your observed data fits your expected data extremely well. In other words, thereisa relationship. A very large chi square test statistic means that the data doesnotfit very well. In other words, there isn’t a relationship. 2、What is a ...
This is a rather large table to compute the test statistic by hand, so let's make RStudio do the work for us! > chisq.test(tbl) b) Copy and paste your output. c) Use the output to write out the four steps of the hypothesis test for independence. Chi...
1. Chi-Square test only works for categorical data (data in categories), such as Gender {Men, Women} or color {Orange, Green, Blue} etc, but not for...Become a member and unlock all Study Answers Start today. Try it now Create an account Ask a question...
Suppose now that it can not make any assumption on the data of the problem, so that it can not approximate the binomial with a Gauss. We solve the problem with the test of chi-square applied to a 2×2contingency table. In R there is the function prop.test. ...