Hypothesis Testing (Practical) 2024 PDF

PHARM 103 (Practical) hypothesis testing & P-value) Fahad Alkenani, BPharm, RPh, MSc, DIPBA, PhD, C-KPI, C-DA Department of Pharmacy Practice, College of Pharmacy, Taibah University 2024-1446 Steps for Hypothesis Testing 1. Define the null and alternati...

PHARM 103 (Practical) hypothesis testing & P-value) Fahad Alkenani, BPharm, RPh, MSc, DIPBA, PhD, C-KPI, C-DA Department of Pharmacy Practice, College of Pharmacy, Taibah University 2024-1446 Steps for Hypothesis Testing 1. Define the null and alternative hypotheses. 2. Choose the level of significance. 3. Choose the appropriate statistical test and compute the test statistic. 4. Compute the p-value. 5. Check whether to reject the null hypothesis by comparing the p-value to the level of significance. 6. Draw conclusion from the test. Example of Null and alternative hypotheses Does a new diabetes treatment reduce blood glucose Research question different than an existing treatment? The null hypothesis (H0) The mean reduction in blood glucose level is the same in the two treatment groups. The alternative hypothesis The mean reduction in blood glucose is different in the (H1) two treatment groups.  Type I and Type II Errors Case 1: In the real world (population): Smoking rate in males = smoking rate in females. H0: Null hypothesis: nothing is happening / no difference H1: Alternative hypothesis: the idea of the researcher. So, H0: Smoking rate in males = smoking rate in females H1: smoking rate in males ≠ smoking rate in females Possible decisions based on the statistical analysis: 1. Accept the null hypothesis and conclude that smoking rate in males = smoking rate in females. (which is the correct decision). 2. Reject the null hypothesis, accept the alternative hypothesis and conclude that smoking rate in males ≠ smoking rate in females. (Here we made a mistake) type I error / false positive / α Here, we made a mistake by rejecting a true null hypothesis and is called type I error, or α. We reached a false positive conclusion.  Type I and Type II Errors Case 2: In the real world (population): Smoking rate in males ≠ smoking rate in females H0: Smoking rate in males = smoking rate in females. H1: smoking rate in males ≠ smoking rate in females. Possible decisions based on the statistical analysis: 1. Reject the null hypothesis, accept the alternative hypothesis and conclude that smoking rate in males ≠ smoking rate in females. (which is the correct decision) 2. Accept the null hypothesis and conclude that smoking rate in males = smoking rate in females. (here we made a mistake) Type II error / false negative / β Here, we made a mistake by accepting a false null hypothesis and is called type II error, or β. We reached a false negative conclusion. Question (1) 1. A statement about the value of a population parameter is called: A. Null hypothesis B. Alternative hypothesis C. Simple hypothesis D. Composite hypothesis Question (2) 2. If Ho is true and we reject it is called: A. Type-I error B. Type-II error C. Standard error D. Sampling error Question (3) 3. Hypothesis Testing is sometime referred as significance testing. A. Yes B. No Question (4) 4. In hypotheses testing, we are asking whether the sample mean is consistent with a certain hypothesis value for the population mean A. Yes B. No Question (5) 5. The purpose of hypothesis testing is to: A. Test how far the mean of a sample is from zero B. Determine whether a statistical result is significant C. Determine the appropriate value of the significance level D. Derive the standard error of the data Question (6) 6. A statement made about a population for testing purpose is called? A. Statistic B. Hypothesis C. Level of Significance D. Test-Statistic Question (8) 8. In a criminal trial, a Type II error is made when: A. A guilty defendant is acquitted (set free) B. An innocent person is convicted (sent to jail) C. A guilty defendant is convicted D. An innocent person is acquitted Question (9) 9. A Type II error occurs when we: A. Reject a false null hypothesis B. A reject a true null hypothesis C. Do not reject a false null hypothesis D. Do not reject a true null hypothesis Question (10) 10. If the null hypothesis is false, then which of the following is accepted? A. Null Hypothesis B. Positive Hypothesis C. Negative Hypothesis D. Alternative Hypothesis. Question (11) 11. The rejection probability of Null Hypothesis when it is true is called as? A. Null Hypothesis B. Level of Significance C. Level of Margin D. Level of Rejection. Question (12) 12. If the Critical region is evenly distributed then the test is referred as? A. Two tailed B. One tailed C. Three tailed D. Zero tailed Question (13) 13. Type 1 error occurs when? A. We reject H0 if it is True B. We reject H0 if it is False C. We accept H0 if it is True D. We accept H0 if it is False