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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.
Create a 95% confidence interval for population proportion of positive drug tests.
Number of miles flown in a One- year period by the sample of "frequent flyers" was recorded. Is this a grouped or an ungrouped frequency distribution?
Why might driver be tempted not to use seat belt "just on this trip"?
What was the highest score earned on the exam? According to Chebyshev's Theorem, how many students scored between 42 and 74?
Explain the strength of relationship between the assets?
The null hypothesis is that the distribution of mother's educational level is the same for both treatment groups. The value of the chi-square statistic is 7.422. Evaluate the P-value
This distribution is positively skewed. The standard deviation of the population is not known.
A company wants to know if minorities are more likely to be in certain job categories than others. Their data base codes employees 1 for clerical, 2 for custodial, and 3 for manager. A logistic equation was fit to the data with SPSS.
Report the t-value, whether you accept or reject Ho, and whether the difference was significant in a brief sentence.
For the 20 test scores shown, find the percentile rank for a score of 86.
When using past data, I have found that the proportion of items rejected by quality control personnel is about 3%. We normally make 5000 items per day. For a p chart, what are the upper and lower control limits?
Give a possible description why serum cholesterol values for older males are lower than for younger males and reverse is true for females.
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