Understanding Statistics: Population vs. Sampling Variability

Fill in the blanks on the following statement: A statistic describes a __________ and a parameter describes a ___________. What is the difference between real and sampling variability? Which of the following is an example of population variability? Which of the following is a correct definition of sampling variability? population; sample sample; population median; mean mean; median Real variability is present only in the population, but sampling variability is in both the population and sample Real variability is present only in the sample, but sampling variability is in both the population and the sample Real variability is present in both the population and the sample, but sampling variability is only in the sample Real variability is present in both the population and the sample, but sampling variability is only in the population Of all the trees in California, 32% are above 10 feet tall, whereas the rest are shorter The U.S. Census is a way to try to measure everyone in the population In a study of 20 mice, some showed fear by hiding while others ran away Each section of Psych 100A has slightly different GPAs Samples that show variability across multiple variables Variability observed in cases on a specific variable within a

Which of the following functions would produce the mean of a variable called height in a dataset called people ? (It's ok if other numbers are produced). Check all that apply. Which of the following is TRUE about the sample mean? Look at the following graphs. Which graph is most likely to have a similar mean and median? sample Variability observed for a statistic across many samples All of the above favstats(people$height) lm(~people, data = height) mean(people$height) median(people$height) There will be the same number of cases with values above and below the mean The distance between points above and below the mean are balanced The mean will always be between Q1 and Q3 The mean is the only way to describe the middle of distribution Graph A Graph B

Which of the follow is the appropriate equation for the simple model? Which of the following code chunks would fit a simple model for the variable height in a dataset called people ? Which of the following is TRUE about the simple model? ( Check all that apply ) B Graph C For all of the above the mean and median should be similar lm(~people, data = height) lm(height~NULL, data = people) lm(~height, data = people) lm(people~NULL, data = height) The variance of the scores is the same as the variance of the residuals in the simple model The simple model predicts the same score for every variable The variance of the predictions is the same as the variance of the residuals in the simple model The simple model predicts the same score for every case

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