For these problems, perform an independence test using the Chi-Square distribution. ? In Minitab, the command is STAT ---> TABLES ---> Cross Tabulation and Chi-Square ? On TI-84, enter the table in MATRIX A, then go to STAT ---> TESTS ---> C: X² Test

Note: it's better to use technology to calculate since manual calculations are very tedious.

#1 Test the claim that number of injuries is independent of stretching before the sports activity. Use level of significance (1 = 0.05 Athlete has Result Stretched Not stretched Injury 18 22 N0 injury 21] 189 Test the claim that restaurant rating is independent of the size of the restaurant. Use level of significance ('1, = 0.01 Rating Size of restaurant Excellent Fair Poor Seats 100 or fcwcr 182 203 165 Seals over 100 180 311 159 Test the claim that Vehicle preference is independent of gender. Use level of significance or = 0.05 Type of car Gender Compact Full-size SUV Truck/van Male 28 39 21 22 Female 24 32 20 14 Test the claim that the number of students achieving basic skills levels in 3 subjects is independent of whether the school is in an urban vs. suburban location. Use level of significance on = 0.01 Subject Location of school Reading Math Science Urban 43 42 38 Suburban 63 66 65 Since P-value > alpha then we fail to reject the Null Hypothesis. Thus we do not reject the claim there is no relationship between taking an online course and gender (these variables are thus independent)