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Can we conclude the mean length of stay of employees at the company differs from the mean length of stay at that dangerous industry?
The mean length of stay of employees in a dangerous industry is 16.7 months. One hundred randomly selected employees at the company had a mean length of stay of 17.8 months. At the 0.05 significance level, do the data provide sufficient evidence to conclude the mean length of stay of employees at the company differs from the mean length of stay at that dangerous industry? Assume that the population standard deviation of lengths of stay in that dangerous industry is 6.0 months.
A sample of approx 25 students enrolled in the university points out that X (bar) = $315.4 and s = $43.20.
Prepare an ANOVA table and test the null hypothesis of no linear relationship between the two variables.
Conduct an analysis of variance
The correct set of hypotheses to test the effect of the bonus plan, the difference between the t and z distributions
Run a multiple regression and interpret all the findings, R 2 , F, IV coefficients, and the intercept. Then in paragraph format, identify and report the following:
Plot a scatter diagram of the results with Depth of Water as the independent variable.
Is the z value positive or negative? Explain why it should be positive or negative.
Suppose that an IQ test was given to a large group of persons, the scores are assumed to be from a normally distributed population, that mean = 100 and s (standard deviation) = 15.
We are interested in testing to see if the variance of a population is less than 7. The correct null hypothesis is:
To forecast attendance at an yearly tennis tournament a model has been developed that uses attendance from the previous year and the amount spent for advertising this year.
Test the overall significance of the regression model at α = .05 level. Please use the six-step hypothesis-testing framework we employed in class, and write out the last three steps in this table:
Would the null hypothesis be accepted or rejected in this case?
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