a. What does it mean when you calculate a 95% confidence interval? * - The random process you used (e.g. experiment/game/survey/etc.) will capture the population value 95% of the time in the long run. - You can be "95% confident" that your interval will include the population value. - You can be "5% confident" that your interval will not include the population value. - All of the above statements are true. b. What would happen (other things equal) to a confidence interval if you calculated a 99 percent confidence interval rather than a 95 percent confidence interval? * - It will be narrower. - It will not change. - The sample size will increase. - It will become wider. c. Standard _______ is used to describe the variability for the average distance that scores deviate from their mean. - statistics - units - deviation - error d. Standard _______ is used to describe the variation of study results, imagining hypothetically you were to repeat a study many times. * - statistics - units - deviation - error e. Why do the intervals have different centers? f. Why do the intervals have different lengths? * g. How many (out of 50) should include the population mean? * h. How many (out of 50) actually include the population mean? *
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A 95% confidence interval for the mean can be interpreted to mean that: Select one: a. you can be 95% confident that you have selected a sample whose interval does not include the population mean b. If all possible samples are taken and confidence intervals are calculated, 95% of those intervals would include the true population mean somewhere in their interval c. if all possible populations are taken and confidence intervals are calculated, 95% of those intervals would include the true sample mean somewhere in their interval d. if all possible samples are taken and confidence intervals are calculated, 95% of those intervals would include the true sample mean somewhere in their interval
Thuc N.
Consider a 95% confidence interval for a population mean. Which of the following is not correct about the confidence interval? a. If we take random samples of same size from same population and compute confidence intervals, the center of each interval is equal to the population mean. b. If we take random samples of same size from same population and compute confidence intervals, about 95% of those intervals would capture the true mean of the population. c. If we take random samples of same size from same population and compute confidence intervals, about 5% of those intervals would miss the true mean of the population. d. If we take random samples of same size from same population and compute confidence intervals, the length of the interval remains the same for all intervals.
Marc L.
1. If we have 2 pairs of measurements of the same quantitative variable for each individual sampled, we can compute A. two confidence intervals, one for each population mean, and compare them. B. a confidence interval for the population mean of one measure and see if it contains the sample mean for the other measurement. C. a confidence interval for the parameter mu_d, the population mean of all pairwise differences. D. a confidence interval for the sample mean pairwise difference. 2. The robustness of the one-sample t procedure for a population mean tells us that A. the procedure is robust because it is valid even when the conditions are not met B. the procedure is valid even if we do not know the value of the population mean mu C. the procedure can be valid when the variable is not Normally distributed regardless of the sample size D. the procedure is valid even if we do not know the value of the population standard deviation sigma E. the procedure can be valid when the variable is not Normally distributed if the sample size is large enough 3. When computing a confidence interval about a parameter based on sample data, what is the impact of using a different confidence level? A. A lower confidence level gives a narrower confidence interval, so it's a good idea to use the lowest confidence level possible. B. No answer text provided. C. A higher confidence level gives a wider confidence interval, therefore it is useless. D. A higher confidence level gives a wider confidence interval, reflecting the higher overall success rate of the method.
Sri K.
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