We conclude with guidelines for improving statistical interpretation and reporting. We then provide an explanatory list of 25 misinterpretations of P values, confidence intervals, and power. We emphasize how violation of often unstated analysis protocols (such as selecting analyses for presentation based on the P values they produce) can lead to small P values even if the declared test hypothesis is correct, and can lead to large P values even if that hypothesis is incorrect. Our goal is to provide a resource for instructors, researchers, and consumers of statistics whose knowledge of statistical theory and technique may be limited but who wish to avoid and spot misinterpretations. In light of this problem, we provide definitions and a discussion of basic statistics that are more general and critical than typically found in traditional introductory expositions. This high cognitive demand has led to an epidemic of shortcut definitions and interpretations that are simply wrong, sometimes disastrously so-and yet these misinterpretations dominate much of the scientific literature. Instead, correct use and interpretation of these statistics requires an attention to detail which seems to tax the patience of working scientists. A key problem is that there are no interpretations of these concepts that are at once simple, intuitive, correct, and foolproof. Remember to include all relevant Minitab Express output.Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. If assumptions are met, use a t distribution to approximate the sampling distribution. Use Minitab Express and the five-step hypothesis testing procedure given below to determine if American men and women differ in the population in terms of the number of friends they have on Facebook on average. Construct a dotplot with groups to compare men and women in terms of the number of Facebook friends they have. Construct side-by-side box plots to compare men and women in terms of the number of Facebook friends they have. Data concerning gender and number of Facebook friends are in the file FacebookGender.MTW.Ī. Step 4: Decide between the null and alternative hypothesesĭata were collected from a random sample of American Facebook accounts. Step 1: Check assumptions and write hypotheses Remember to copy+paste all relevant Minitab Express output. If assumptions are met, use the normal approximation method. Use Minitab Express and the five-step hypothesis testing procedure given below to determine if there is evidence of a difference between the proportions of all Penn State Shenango and all Penn State World Campus students who are attending full-time. Always clearly identify your final answer. Use Minitab Express to construct a 95% confidence interval to estimate the difference between the proportions of all Penn State Shenango and all Penn State World Campus students who are attending full-time.
In a random sample of 40 World Campus students, 13 were attending full-time.Ī. In a random sample of 35 Penn State Shenango students, 17 were attending full-time. Reminder: The standard error is computed differently for a two sample proportion confidence interval and a two sample proportion hypothesis test. If you have any questions, post them to the course discussion board.
P VALUE MINITAB EXPRESS FULL
Output without explanation will not receive full credit and answers with no output or explanation will not receive full credit. If you do hand calculations show your work using the Word equation editor. If you use Minitab Express or StatKey include the appropriate output (copy + paste). Full credit will not be given to answers without work shown. Answer the following questions showing all work.
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