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Chi square test

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Chi-square goodness-of-fit test
Does it seem to you that people tend to be absent more on some days of the week than on others? Recently, a major biotechnology firm collected data with the hope of determining whether or not its employees were more likely to be absent (due to personal reasons or illness) on some weekdays than on others. The firm examined a random sample of employee absences.
The distribution of these absences is shown in Table 1 below. The observed frequencies for each category (each weekday) are shown in the first row of numbers in Table 1. The second row of numbers contains the frequencies expected for a sample of employees if employee absences at the firm are equally likely on each of the five weekdays. The bottom row of numbers in Table 1 contains the values

= (Observed frequency - Expected frequency)2

Expected frequency

for each of the categories.
Fill in the missing values of Table 1. Then, using the level of significance, perform a test of the hypothesis that employee absences at this firm are equally likely on each of the five weekdays.
Round your responses for the expected frequencies in Table 1 to at least two decimal places. Round your responses in Table 1 to at least three decimal places.
Table 1: Information about the sample

Monday Tuesday Wednesday Thursday Friday Total
Observed Frequency (f0) 29 25 25 24 37

Expected Frequency (fE) 28.00 28.00 28.00
(f0 - fE)2
fE 0.321 0.571 2.893
What type of test statistic is used here?

What is the value of the test statistic?

What is the p-value?


Solution Summary

The solution provides step by step method for the calculation of chi square test . Formula for the calculation and Interpretations of the results are also included.