Recall that to construct a confidence interval for the mean when the population standard deviation is unknown, the popul

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Recall That To Construct A Confidence Interval For The Mean When The Population Standard Deviation Is Unknown The Popul 1 (65.97 KiB) Viewed 85 times

Recall that to construct a confidence interval for the mean when the population standard deviation is unknown, the population must follow the normal probability distribution. To test this condition, the following data show a random sample of weekly visits by patients to a chiropractic office. Complete parts a and b below. E: Click the icon to view the weekly patient visit data. x Observed weekly patient visits O A. Ho: The number of weekly patient visits does not follow the normal distribution. Hy: The number of weekly patient visits follows the normal distribution. O B. Ho: The mean number of weekly patient visits is 101.5. Hy: The mean number of weekly patient visits is less than 101.5. OC. Ho: The mean number of weekly patient visits is 101.5. H,: The mean number of weekly patient visits is greater than 101.5. OD. Ho: The number of weekly patient visits follows the normal distribution. H4: The number of weekly patient visits does not follow the normal distribution. 75 97 106 131 118 121 121 82 121 98 135 74 92 104 120 79 96 112 102 84 97 70 94 112 123 75 97 109 82 111 105 93 102 113 Use the following intervals to calculate the chi-square test statistic, x? Interval 1: Zs - 1.0 Interval 2: -1.0< Z SO Interval 3: 0< Z 51.0 Interval 4: Print Done 1.0<z The chi-square test statistic is y2 = (Round to two decimal places as needed.) The chi-square critical value is xa =D (Round to three decimal places as needed.) Draw the proper conclusion. the null hypothesis. There Venough evidence to conclude that the number of weekly patient visits b. Determine the p-value and interpret its meaning. The p-value is (Round to three decimal places as needed.) Interpret the p-value The p-value is the probability of observing a test statistic the part a statistic, assuming