Statistics

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A researcher wants to see if gender plays a role in where we sit in a restaurant. An analysis of survey data yields the following contingency table, chi-squared value, and p-value:

Tabulated statistics: Gender, Seating

Rows: Gender Columns: Seating

Back Front Middle All

Female 14 28 84 126
Male 18 18 63 99
All 32 46 147 225

Pearson Chi-Square = 2.469, DF = 2, P-Value = 0.291

a. What is the interpretation of the p-value for the Chi-Squared Statistic value of 2.469?
There is no realtionship in this population

b. What is the conclusion based on the p-value?

my answer: the p value is a probability

c. What are the null and alternative hypotheses for this Chi-Squared Test?

My answer: the null- More males sit in the front and middle in restaurant
Alternative : the females sit in the back of the restaurant

• Statistics -

b. What level of significance are you using? If P ≤ .05, then there is a relationship. You reject the null hypothesis. If P ≤ .01, you do not reject.

c. Ho(null): There is no relationship between gender and where people sit in a restaurant.

Ha: There is a relationship between gender and where people sit in a restaurant.

• Statistics -

What is the interpretation of the p-value for the Chi-Squared Statistic value of 2.469?
-- were do I go from here on this one??

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