Final answer:
The null hypothesis in question 26 likely states there is no significant difference or effect between groups or conditions. Since the decision was not to reject the null hypothesis, there is insufficient evidence to support the alternative hypothesis at the given significance level.
Step-by-step explanation:
Regarding question 26, which asks for the calculation of the test statistic and p-value, the null hypothesis would typically be a statement of no effect or no difference.
Based on the context given, specifically the conclusion mentioned that states 'there is not sufficient evidence to conclude that the absent days do not occur with equal frequencies,' it seems that the null hypothesis posits that the different categories being compared have equal frequencies or means.
While we aren't given the exact specifications of question 26, the null hypothesis () for a typical hypothesis testing scenario like this would often be defined as 'no significant difference exists.'
Therefore, if the decision is not to reject the null hypothesis, then the conclusion would be that the sample data does not provide strong enough evidence to show a statistically significant difference from what was specified in the null hypothesis at the chosen level of confidence.
In hypothesis testing, the p-value is used to determine the probability of obtaining a result at least as extreme as the one observed, given that the null hypothesis is true. A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you would reject the null hypothesis.