1. Respond to the following in a minimum of 175 words:
Let’s use the checkpoint. The 7,000 is in error. The correct chi square is 7.2.
Let’s discuss the checkpoint and Chi Square in general.
2. Respond to classmate Lisa Raney to her DQ response. (90 words)
Instructor and Class,
There are two types of chi-square tests and they are used for different purposes. 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 general terms a chi-square tests to see whether distributions of categorical variables differ from each other. A very small chi-square test statistic means that your observation data fits your expected data extremely well and there is a relationship. A very large chi-square test statistic means that the data does not fit well and there is no relationship. A chi-square statistic is a way to show a relationship between two categorical variables. The two types of variables in statistics are numerical and non-numerical. The chi-square statistic is a single number that tells you how much difference exists between your observed counts and the counts you would expect if there were no relationship at all in the population. The chi-square statistic can only be used on numbers. For example if you have 10% of 200 before the chi-square test can be conducted the number has to be converted to the number 20. In short a chi-square statistic is used for testing hypotheses (Chi-Square Statistic, 2019).
I used the equation: 16/10.0*6.0=9.6 and 4/10.0*-6.0=-2.4    9.6- -2.4=7.2 chi-square
Reference