Question

Based upon the input from Units 1 and 2, you have just received your next assignment that will contribute to your next decision. For the outdoor sporting goods client, based upon your prior decision on whether or not to either expand to the next market or retain your current position, justify your decision further utilizing the Chi-Square Distribution tool. One key criterion point: You do not have adequate data to formulate a full Chi-Square for the outdoor sporting goods client. However, you do have sufficient data to initiate this process. You are charged to demonstrate the initial steps of a nonparametric test that are qualitative. Utilizing the null and alternative hypothesis, further present your justifications for your selection and what it means beyond the mere formulas. What is this going to tell the Board of Directors and contribute to the decision-making process?

The following information may be helpful in understanding Chi-Square and hypothesis testing:

Chi-Square and Hypothesis Testing

Please review this helpful video. The presenter uses the "flip of the coin" and the "role of the die." These are examples and analogies used in the CTU resources.

The following are assumptions you might make in this assignment that might make the assignment more helpful and make the responses more uniform:

Continue to utilize the Big D scenario. Work under the assumption that the sample is based upon two different proposed product lines.

Additionally, work under the assumption that the same demographics are utilized for each product. 

Answer 1

Hypothesis: My prediction is that either expand to the next market and the other possible outcome is that retain your current position. These are our hypothesis. Our alternative hypothesis is retain your current position because we set alternative hypothesis equal to what we want to prove. The null hypothesis is the opposite one, generally null hypothesis is the statement of no difference. For example,
Null Hypothesis Ho : There is no significant difference between mean and sample population

Alternative Hypothesis H1: There is significant difference between mean and sample population

Level of significance: a : there’s a 5% risk of rejecting the null hypothesis when there is no difference between the sample and population mean

In a non-parametric test, the observed sample is converted into ranks and then ranks are treated as a test statistic.

In non-parametric tests, we use the ranks to compute the test statistic.

After setting the degrees of freedom and critical values, the decision of accepting or rejecting the null hypothesis will be made.

We use Chi square as the comparison is between 2 possibilities.
As we get our data, we can compute the value of chi square x2 and from the table of degrees of freedom and critical values, be 95% sure of decision of expanding to next market or retaining the current position.