t-Tests.
Imagine a shift manager at a manufacturing plant is gathering data on the number of units workers assemble during two different shifts over 10 different days. If the number of units assembled by each shift varies greatly from day to day, what impact will that have on the likelihood of a significant difference between the two shifts? Explain and support your response.
ANOVA Testing.
The manager of an agency providing temporary employees to city offices is analyzing the number of days temporary hires typically work in various types of industries.
The data are as follows:
Legal clerical: 2, 1, 4, 4, 2, 5, 6
Accounting firms: 3, 6, 4, 5, 5, 7, 8
Insurance: 5, 4, 7, 9, 9, 8, 11
Using the data above, answer the following questions:
a. Are there significant differences in the length of time temporary employee’s work in the different industries?
b. How much of the differences can be explained by the industry?
c. Which groups are significantly different from others?
d. Why would a manager be focused on measuring the number of days that a temporary works each week?
