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Why is the population shape of concern when estimating a mean? What does sample size have to do with it? Explain
Define the standard error of the mean. What happens to the standard error as the sample size increases? Explain
Explain the purpose of the chi-square test for independence. Provide some practical examples where this test might be used in business.
Below you are given a partial computer output based on a sample of 16 observations.
Madison Metals recently reported $9,000 of sales, $6,000 of operating costs other than depreciation, and $1,500 of depreciation. The company had no amortization charges and no non-operating income.
Within distribution of scores, measures of dispersion give an indication of?
A researcher believes that if she uses a different text the students will score differently on the standardized test but she doesn't know what the difference is. The test had a mean of 110 and a σ of 12.
Without constructing the 98% confidence interval for the rate of effectiveness, would you expect the interval to be longer or shorter compared to the 95% confidence interval? Why?
Normal distribution of 5 pounds per square inch, standard deviation of 1.5 pounds per square inch, what proportion have less that 3.17 pounds per square inch, at least 3.6 pounds, are between 5 and 5.5 and 95% will be contained between what two va..
Make a List of type of possible errors. Assume that you were interested in knowing the mean score for a certain quiz in a statistics class.
A personnel manager for a large corporation feels that there may be a relationship between absenteeism and age and would like to use the age of a worker to develop a model to predict the number of days absent during a calendar year.
It does not matter, when data are skewed mean and median are the same.
The caffeine content of 20 brands of regular coffee is shown below. 80 82 89 85 87 30 33 44 40 46 50 55 60 62 71 90 92 75 63 65. Thus, this job helps to construct a Frequency Distribution with a class interval of 10, starting with 30.
Multiple choice question using Forecasting techniques. Which among of the following models are best suited to forecast a time series with a stable seasonality component.
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