You are conducting a test of independence for the claim that there is a relationship between favorite ice cream flavor and gender. Use a significance level of .01. Vanilla Chocolate Strawberry Male 32 67 37 Female 24 40 25 The expected observations for this table would be (Round to 3 decimal places.) Vanilla Chocolate Strawberry Male Female At the .01 significance level, what is the critical chi-square for this data? (Round to 3 decimal places.) Xc What is the chi-square test-statistic for this data? (Round to 3 decimal places.) x² : What can you conclude about Gender and Favorite Ice Cream Flavor? O Gender and Ice Cream Flavor are Dependent O Gender and Ice Cream Flavor are Independent

Need C and D

Please help I need in an hour Thankyou so much

Find the test statistic and p value

Question: Can you give an example of variable for which  the mean would not be appropriate to describe the data (that is, tell me a circumstance in which you would not want to use the mean to describe a dataset).

You developed a way to measure anger people.  Test the claim that the mean score of anger for younger people is equal to the mean score for older people. Use a significance level of .06.  The scores are listed below. Scores for younger people: 25, 33, 19, 8, 39, 29, 28, 18, 41, 3, 27, 35, 14, 25, 36, 4, 11 Scores for older people: 38, 35, 21, 5, 19, 22, 35, 33, 54, 3, 55, 9, 15, 22, 47, 4, 21

need   C and D  please

Please no written by hand

A survey was developed to estimate the average number of hours per week that adults spend exercising.  Every third person entering a large fitness complex was surveyed, with a total of 2,500 people being surveyed.  The data showed that the mean number of hours spent exercising was 3.2 hours per week.  Which characteristic of the survey could create a bias in the results?      The size of the sample  The size of the sample  The method of analyzing the data  The method of analyzing the data  The method of choosing the people who were surveyed  The method of choosing the people who were surveyed  The size of the population

You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age 65 69 48 37 49 27 62 64 Ho: p = 0 Ha: p = 0 r= Find the p-value p-value= Number of Driver Deaths per 100,000 22 22 34 Find the Linear Correlation Coefficient The p-value is Greater than a Less than (or equal to) a 23 28 20 The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho 33 33 The conclusion is O There is a significant negative linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. O There is a significant positive linear correlation…