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a) construct a 95% confidence interval for the population mean, μ. assume the population has a normal distribution. In a random sample of 26 computers, the mean repair cost was $137 with a standars deviation of $35.
b) suppose you did some research on repair costs for computers and found that the standard deviation is σ=35. Use the normal distribution to construct a 95% confindece interval for the population mean, μ. compare the results.
Suppose that you select a 50 families sample. Which is the form expected from the distribution of the average or median of the sample?
Why is sampling strategy important? Please provide one or two examples from your work or past experience?
In a study of the lizard Sceloporis occidentalis, researchers examined field-caught lizards for infection by the malarial parasite Plasmodium. To help assess the ecological impact of malarial infection, researchers tested 15 infected and 15 noninf..
Many people believe that abnormal behavior is more likely to occur during a full moon. As a test for empirical evidence to support this belief, a study was conducted based on admission of new clients over a one year period by lunar phases:
You want to create a 90% confidence interval for the true average number of yards per game he throws. What is the margin of error for this estimate?
It is impossible to obtain a standard error less than 2 for any sized sample.
Why do you use the chi-square statistic? Explain. What type of data is used with chi square analysis? Explain. What are the hypotheses in a chi-square test for independence? Explain.
What is the probability that the drug will be effective for 3 hours or more?
Give a 95% confidence interval for the mean of the population from which the sample is drawn.
Compute the 99% confidence interval for the population mean based on the sample 62, 68, 61, 64, 65, 62, and 66. Then, change the number from 66 to 16 and calculate the confidence interval.
The probability that a patient recovers from a disease is 63%. What is the probability that:
A fellow researcher fits a simple linear regression model Yi = α + βXi + ui by least squares, but has doubts that the first least squares assumption E(ui |Xi) = 0 is correct for her data set.
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