Question

Based on your analysis in understanding the seasonality (month to month variation) of the business, the degrees of freedom (which is needed for tukey test) within groups is?

1) 1
2) 2
3) 3
4) 4

Answer 1

The degrees of freedom within groups for monthly variation would normally be the number of observations minus the number of months (groups). However, the provided options (1, 2, 3, 4) are not typical for such analyses, and without more information, it is not possible to determine the correct number of degrees of freedom from the given options.

Step-by-step explanation:

To understand the degree of seasonality and the corresponding degrees of freedom (needed for statistical tests such as the Tukey test), it is important to first understand how degrees of freedom are calculated in different statistical scenarios. For most cases involving analysis of variance (ANOVA), where the Tukey test is often used, the degrees of freedom within groups are calculated by subtracting the number of groups from the total number of observations.

If we are conducting such an analysis on month-to-month variation for a business, and we have 12 months, then the degrees of freedom within groups would be the number of observations across all months minus 12 (the number of groups, which is one for each month). However, without the exact number of observations, we cannot calculate the degrees of freedom. The options given (1, 2, 3, 4) do not correspond to typical month-to-month analyses, since the degrees of freedom are usually higher.

In general, when conducting a test of independence such as chi-square, the degrees of freedom are calculated as (number of columns - 1)(number of rows - 1), according to section 11.3 Test of Independence. This means that if we were looking at a 12-month analysis with two variables (e.g., revenue and expenses), the degrees of freedom would be (12-1)(2-1) = 11.