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Nevertheless, some examples in which a one-sample t-test may be useful are: These questions may be interesting, but they don’t occur all that often in research or practice, and selecting an arbitrary value to test isn’t typically informative.
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Is the job satisfaction of a company’s employees significantly different than a 4 on a 1 to 7 scale?.Is a company’s yearly revenue significantly different than 10 million dollars?.Is a basketball team’s average height significantly different than 6’6″?.It tells us whether the mean of a variable is significantly different than a chosen value, and it can be used to answer the following questions: If you have any questions, please email me at purpose of a one-sample t-test is pretty simple. Nevertheless, we can trick Excel into performing it for us, which I detail below. I get slightly annoyed whenever I teach it, though, because Excel does not have the one-sample t-test built into its Data Analysis add-on. However, it is a very good entry into learning about two-sample t-tests and ANOVAs, so I teach it early in my undergraduate statistics courses. Partc Level of Significance 0.I don’t come across the need to perform a one-sample t-test that often, whether in research or practice. What is the value of the F test statistic? (to 4 decimals) What is the p-value? (to 4 decimals) P-value is so the addition of the two independent variable atistically significant. 05 level of significance, test to see whether the addition of the interaction term and the smoker variable contribute significantly to the estimated regression equation developed in part (a). The regression equation is Age + Risk (to 2 decimals) Pressure + CSmoker +| AgePress R= (to 3 decimals) R' = (to 3 decimals) R-sq adj = 0 (to 3 decimals) c. Note: report Rand R-sq adj between 0 and 1. Develop an estimated regression equation using these four independent variables. Consider adding two independent variables to the model developed in part (a), one for the interaction between age and blood-pressure level and the other for whether the person is a smoker. The regression equation is Age + Pressure Risk = (to 2 decimals) R? (to 3 decimals) R-sq adj (to 3 decimals) (to 3 decimals) b. Develop an estimated regression equation that can be used to predict the risk of stroke given the age and blood-pressure level. Construct a spreadsheet to answer the following questions. For the smoker variable, 1 indicates a smoker and O indicates a nonsmoker. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period.
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Data from a portion of this study are contained in the Excel Online file below. Screenshot of ToolPak A 10-year study conducted by the American Heart Association provided data on how age, blaad pressure, and smoking relate to the risk of strokes. Transcribed image text: Due to a recent change by Microsoft you will need to open the XLMiner Analysis ToolPak add-in manually from the home ribbon.