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Scores are obtained from the Law School Admission Test (LSAT) are normally distributed with a mean score of 550 and a standard deviation of 110.
1. If a test score is selected at random, find the probability that it is less than 750.
2. If the top 15% of the test scores are usually good enough for admission to law school, find the cut off score for gaining admission.
Explain why we need to use the t distribution. What assumption do you need to make?
Then estimate demand again with a weighted moving average in which sales in the most recent year are given a weight of 2 and sales in the other two years are each given a weight of 1.
If we are dealing with non-normal data we use Chebychev's Theorem. While not as precise, it does provide some level of utility. If we use Chebychev
If the observed value is 4, the expected value is 5, and the standard error is 4, then the test value used for the z test is equal to
Determine the cost Xs to develop the support system for which the probability of exceeding Xs is equal to 0.01?
The grade point average of the students at UTC is 2.80 with a standard deviation of 0.84. The grade point average of students at UTK is 2.4 with a standard deviation of 0.84. Which university shows a more dispersed grade distribution?
Any value which is based on having measured a sample is called:
Write down the name of 4 parts of the regression equation.
Could you explain the Pearson or product-moment correlation? If we were to use a partial correlation, would you want to look at the relationship between two variables while removing the effect of one or two other variables?
What is the point estimate of the proportion of the population of employees who strongly dislike their current work experience (to 2 decimals)?
Say, for example, the correlation is 0.75 between Height (measured in inches) and Weight (measured in pounds). If Height were changed to being measured in centimeters (where 1 inch = 2.54 centimeters) what effect would this have on the correlation..
Discuss the assumptions of this model. Specifically, how does each variable affect demand? How do the variables influence each other? What limitations might this model have? How can it be improved?
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