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1. Why do the critical values from the Chi-square distribution get larger as the degrees of freedom get larger? Recall that this is opposite the pattern for the t-table.
2. Why is choosing sample size important(with specific reference to proportions)?
To test whether there is a significant mean difference among the three.
What is the most controllable method of increasing the precision (narrowing) of the confidence interval? What percentage of times will the mean (population proportion) not be found within the confidence interval?
Generate survival times X from an exponential distribution with rate lambda=1 with a censoring distribution C being exponential with rate theta = 2/3. Then Plot Kaplan-Meier Survival curve estimates along with true survival curve for n=25,100,1000..
One of the problems encountered by corporations in America is finding an adequate number of employees who want to move into management. Recent surveys of workers in America taken by the Department of Labor in Washington D. C.
A scientist examined the effect of temperature and catalyst on the yield of a reaction. He ran the experiment at both 150° and 200°C with two types of catalyst.
Estimating the individual score using normal distribution and find the minimum SAT score needed to be accepted?
A local bank wants to install motion detector burglar alarms. Each has a 70% chance of detecting a burglar. If the bank wants to be 99% certain of detecting a burglar how many need to be installed?
Compute a 90% confidence interval for the population mean, based on the sample 25, 27, 23, 24, 25, 24, and 59. Change the number from 59 to 24 and recalculate the confidence interval.
If we have 2 groups with 2 characteristics each, what would our critical value be with an alpha of .025?
Normal distribution has mean of 80 and standard deviation of 14. Find out the value above which 80 percent of values will occur.
An internal study by the Technology Services department at Lahey Electronics revealed company employees receive an average of 6.0 emails per hour. Assume the arrival of these emails is approximated by the Poisson distribution.
Construct a frequency distribution of the sample mean, and plot a histogram of this distribution. Use the central limit theorem to calculate and identify the sampling distribution of the sample mean.
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