A walk-in medical clinic believes that arrivals are uniformly distributed over weekdays (Monday through Friday). It has collected the following data based on a random sample of 100 days. Frequency Mon 25 Tue 22 Wed 19 Thu 18 Fri 16 Total 100 Assuming that a goodness-of-fit test is to be conducted using a 0.10 level of significance, the critical value is:

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Answer:

The degrees of freedom are given by;

[tex] df =n-1= 5-1=4[/tex]

The significance level is 0.1 so then the critical value would be given by:

[tex] F_{cric}= 7.779[/tex]

If the calculated value is higher than this value we can reject the null hypothesis that the arrivals are uniformly distributed over weekdays

Step-by-step explanation:

For this case we have the following observed values:

Mon 25 Tue 22 Wed 19 Thu 18 Fri 16 Total 100

For this case the expected values for each day are assumed:

[tex] E_i = \frac{100}{5}= 20[/tex]

The statsitic would be given by:

[tex] \chi^2 = \sum_{i=1}^n \frac{(O_i-E_i)^2}{E_i}[/tex]

Where O represent the observed values and E the expected values

The degrees of freedom are given by;

[tex] df =n-1= 5-1=4[/tex]

The significance level is 0.1 so then the critical value would be given by:

[tex] F_{cric}= 7.779[/tex]

If the calculated value is higher than this value we can reject the null hypothesis that the arrivals are uniformly distributed over weekdays

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