A major credit card company is investigating whether the distribution of the number of credit cards used by its customers has changed from last year to this year. Customers are classified as using 1 card, 2 cards, or more than 2 cards. The company conducts a chi-square goodness-of-fit test to investigate whether there is a change in the distribution of number of cards used from last year to this year. The value of the chi-square test statistic was

C) If the null hypothesis were true, there is a 2 percent chance of obtaining a chi-square value of at least 7.82.

Step-by-step explanation:

The value of the chi-square test statistic was 7.82 and the p- value is 0.02. This means that if the null hypothesis were true there is a 2 percent chance of obtaining a chi square value of at least 7.82

The p- value is defined as obtaining the test statistic under H0 as extreme as observed.

When the p- value is less than 0.05 in the chi square goodness fit test it means that the null hypothesis is rejected.

There fore option C is the best answer.

A)There is a 2 percent chance that the company's claim is correct.

B) There is a 2 percent chance of obtaining a chi-square value of at least 7.82.

C) If the null hypothesis were true, there is a 2 percent chance of obtaining a chi-square value of at least 7.82.

D) If the null hypothesis were true, there is a 2 percent chance that the company's claim is correct.

E)  If the null hypothesis were true, there is a 2 percent chance of obtaining a chi-square value of 7.82.

no one knows lol

step-by-step explanation:

is there any photos or whatever?