Simulate sampling from the population described in Exercise 6.3 by marking the values of x, one on each of four identical coins (or poker chips, etc.). Place the coins (marked 0, 2, 4, and 6) into a bag, randomly select one, and observe its value. Replace this coin, draw a second coin, and observe its value. Finally, calculate the mean x for this sample of n = 2 observations randomly selected from the population (Exercise 6.3, part b). Replace the coins, mix them, and, using the same procedure, select a sample of n = 2 observations from the population. Record the numbers and calculate x for this sample. Repeat this sampling process until you acquire 100 values of x-bar. Construct a relative frequency distribution for these 100 sample means.
Compare this distribution with the exact sampling distribution of x found in part e of Exercise 6.3.
Answer to relevant QuestionsRefer to Exercise 6.5 and find E(x) = μ. Then use the sampling distribution of x-bar found in Exercise 6.5 to find the expected value of x-bar. Note that E(x-bar) = μ. In exercise Refer to Exercise 6.7, in which we found the sampling distribution of the sample median. Is the median an unbiased estimator of the population mean μ? Refer to The American Statistician (May 2001) study of female students who suffer from bulimia, presented in Exercise. Recall that each student completed a questionnaire from which a “fear of negative evaluation” (FNE) ...A random sample of 40 observations is to be drawn from a large population of measurements. It is known that 30% of the measurements in the population are 1’s, 20% are 2’s, 20% are 3’s, and 30% are 4’s. a. Give the ...An article in Industrial Engineering (August 1990) discussed the importance of modeling machine downtime correctly in simulation studies. As an illustration, the researcher considered a single-machine-tool system with repair ...
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