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You're operating a business in very competitive market. You're not yet the dominant player, but you have invested heavily in marketing and product development and it has paid off with a steady growth rate of 10%. You anticipate that this will continue into the foreseeable future and you are determined to improve your position in this market.
You have carefully defined and analyzed your market and have determined that you currently have 20% market share but the market is stable; that is, it isn't growing and you don't anticipate that it will grow in the future.
What percent of the market do you anticipate having three years from now, given the conditions outlined above?
How can you or your department decide whether or not the variation is important? How could using a mean difference test help?
The quality-control inspector of a production plant will reject a batch of syringes if two or more defective syringes are found in a random sample of eight syringes taken from the batch. Assume the batch contains 1% defective syringes.
A data source generates hexadecimal characters. Let X be the integer value corresponding to a hex character. Suppose that the four binary digits in the character are independent and each is equally likely to be 0 or 1.
Prediction interval for the regression line - Using the age and sick days data from table below, find the 98% prediction interval when x = 47 years.
Determine the point estimate? Give the symbol and value.
Find the 99% confidence interval for the population proportion.
To find out the probability that the age of a randomly selected CEO. The average age of CEOs is 56 years. Suppose the variable is normally distributed.
Testing for Population mean - determine if there has been a significant change in the population mean.
Test whether there is a statistical difference between the two proportions at the 5% significance level.
Sampling distributions. Given a normal distribution with μ = 50 and standard deviation σ = 9, if a sample of n = 100 is selected.
Compare your best difference to the result from an ordinary two-sample t-test between these groups. Comment the difference.
What is the probability that a randomly selected automobile manufactured by the company will have a defective microprocessor?
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