Question

think of a research scenario in which the data would be analyzed using Chi-Square (two variables measured at a nominal level).

Provide a brief research scenario, much like those found in assignment problems.

Identify the independent (antecedent) and dependent (criterion) variables.

Discuss how you would operationally define those variables.

Identify who your participants would be and the steps you would need to take to ensure that your research adheres to ethical standards.

Discuss how aspects of your research design and your measurement choices could potentially affect the internal and external validity of your study. Suggest ways you could try to control for these things.

Answer 1

? A chi-squared test is any statistical hypothesis test where the sampling distribution of the test statistic is a chi-squared distribution when the null-hypothesis is true. 'chi-squared test' often is used as short for Pearson's chi-squared test. The test is used to determine whether there is a

significant difference between the expected frequencies and the observed frequencies in one or more categories.

? In the standard applications of the test, the observations are classified into mutually exclusive classes, and there is null hypothesis, which gives the probability that any observation falls into the corresponding class. The purpose of the test is to evaluate how likely it is between the observations and the null hypothesis.

? Chi-squared tests are often constructed from a sum of squared errors, or through the sample variance. Test statistics that follow a chi-squared distribution arise from an assumption of independent normally distributed data, which is valid in many cases due to the central limit theorem. A chi-squared test can be used to attempt rejection of the null hypothesis that the data is independent.

? The chi- test is a test in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi squared distribution as closely as desired by making the sample size large enough.

There are two types of chi-square tests. Both use the chi-square statistic and distribution:

? A chi-square goodness of fit test determines if a sample data matches a population.

? A chi-square test for independence compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another.

? A very small chi square test statistic means that your observed data fits your expected data extremely well. In other words, there is a relationship.

? A very large chi square test statistic means that the data does not fit very well. In other words, there isn’t a relationship.