Note: Data entry and confidence interval calculation process for a difference in proportions is similar. STEP 1: Enter the original sample data into StatKey by clicking on Edit Data. Enter the sample size and the count/frequency for each sample in the dialog box. STEP 2: Generate several thousand samples (say, 10,000 samples) by clicking on the Computation of a Confidence Interval for a Risk Ratio. RR = p 1 /p 2. Compute the confidence interval for Ln (RR) using the equation above. Compute the confidence interval for RR by finding the antilog of the result in step 1, i.e., exp (Lower Limit), exp (Upper Limit). Note that the null value of the confidence interval for the relative risk Under Perform, choose Confidence interval for μ. By default StatCrunch has a value of 0.95 for the Level input which will produce a 95% confidence level for the population mean, μ. Changing this value to 0.99 would produce a 99% confidence interval. Leave the Level at the default 0.95 and click Compute!. Now instead of a P-value and test
Confidence Interval for Proportion p is the population proportion (of a certain characteristic) To find a C% confidence interval, we need to know the z-score of the central C% in a standard-normal distribution. Call this 'z' Our confidence interval is p±z*SE(p) p is the sample proportion SE(p)=√(p(1-p)/n ^ ^ ^ ^
Use Appendix D to find the values of Student’s t. (a) Construct an interval estimate of μ with 98% confidence. (Round your answers to 3 decimal places.) The 98% confidence interval is from 782.1458 to (b) Construct an interval estimate of μ with 98% confidence, assuming that s = 20. (Round your answers to 3 decimal places.)
Chapter 8 Confidence Intervals (Mean) You intend to estimate a population mean with a confidence interval. You believe the population to have a normal distribution. Your sample size is 27.Find the critical value that corresponds to a confidence level of 90%. (Report answer accurate to three decimal places with appropriate rounding.)
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    • how to find 98 confidence interval