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In practice, people do not know the population mean like you did in step 2 and do not have several estimates to get a sampling distribution of a sample mean. Suppose you have only one sample. In that case you would need to use theoretical results.
If you have studied the central limit theorem, find the margins of error associated with a chance of .90 and a chance of .95. Compare these values with those calculated in step 2.
Explain why we need to use the t distribution. What assumption do you need to make?
1 how many ways are there to select a subcommittee of 7 members from among a committee of 21?2 you have 85 friends with
Test the hypothesis H0:µ X‾ and s: (a) X‾= 44, s = 10, (b) X‾= 43, s = 10, (c) X‾ = 43, s = 2.- Repeat given Exercise, except test H0:µ > 42.
What sample size would allow us to increase our confidence level to 95% while reducing the margin of error to only 3 hours? Round up to the nearest whole number
Give a 95% confidence interval for the difference between the population recovery rates. What can you conclude from this confidence interval?
State the null hypothesis and determine the ANOVA table. What is the result of the F test? Apply Tukey's HSD test to see which means differ if the ANOVA was significant at the 5% level.
for a given wind turbine the probabilities of failure to component a b and c follow the rule 325. the respective
Choose the Hypothesis. Specify the Decision Rule. Calculate the Test Statistic. Make the Decision. Give an interpretation of the Decision
Which of the following statements isn't a property of the normal probability distribution? Please explain briefly why
a. Compute the mean and standard deviation for the time to complete calls to English-speaking service representatives. b. Compute the mean and standard deviation for the time to complete calls to Spanish-speaking service representatives.
Solve the differential equation, 12y=by-4y' writing the solution as y as a function of x (isolating y).
Market researchers use it by correlating product attribute ratings with a dependent measure such as overall satisfaction. They then rank the product attributes to determine which attributes are the most important. They call this Key Driver Analysi..
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