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A surgical technique is performed on seven patients. You are told there is a 70% chance of success. Find the probability that the surgery is successful for at least four patients.
Suppose that the population of heights of male college students is approximately normally distributed with mean m of 68 inches and standard deviation s of 3.75 inches. A random sample of 16 heights is obtained.
At the 0.05 level of significance, is there evidence of a significant relationship between the age groups and where people primarily get their news? If so explain the relationship.
Processing an order for more disks cost $15. Zip uses 60000 disks annually, and the company has a 25% cost of capital. (a) Find the optimal order quantity.
It took a contractor 5000 hours to manufacture their first unit of an item. If the contractor expects to achieve a 94% unit learning curve, how many hours would be required to manufacture units 76-100?
Using an alpha of .05, what can you conclude about homogeneity of variance from the output? Word process your responses on the SPSS output pages.
To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments. You are given the results below.
The bank wants to find out the waiting time of their customers during the Friday evening hours from 5pm to 8pm. Using the data in ungrouped form, compute the Standard Deviation, using the computational formula.
Why is effective sampling important when performing a hypothesis test? What could happen if your sample is not appropriate to your study?
Below, explicitly state slope of your trend line and describe what value of slope signifies in terms of this context.
A manufacturing process makes items whose weights are normally distributed. It is known that 22.57% of all the items made weigh between 100 grams up to mean and 49.18% weigh from the mean up to 190 grams. Find out the standard deviation.
The estimated simple linear regression equation minimizes the sum of the squared deviations between each value of Y and the line.
Describe the difference in the fit provided by the two estimated regression equations.
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