Solution:(b) In this step, you establish the null hypothesis, which typically states that there is no association between the two characteristics being studied. The null hypothesis is a starting point for statistical testing.
(c) Create a contingency table that organizes the data based on the two characteristics under investigation (e.g., Gender and discomfort due to humidity). This table displays the frequencies or counts of observations in each combination of categories.
(e) Using the marginal totals from the contingency table and assuming independence (no association), calculate the expected frequencies for each cell in the table.
(d) For each cell in the contingency table, calculate the squared difference between the observed and expected frequencies, divide this by the expected frequency, and sum these values across all cells.
(a) Once you have the calculated Chi-square statistic from step 4, compare it with the critical or tabulated value from the Chisquare distribution table.
If the calculated value is greater than the critical value, you may reject the null hypothesis, suggesting a significant association between the two characteristics.