Statistical test used: (\chi^2) test of independence (2×2 contingency table).
All expected cell counts were (>5), so the standard (\chi^2) approximation is valid.

With a p-value of 0.124, we fail to reject the null hypothesis at the conventional (\alpha = 0.05) level. There is no statistically significant evidence of an association between gender and self-reported hay fever in this sample.

Below is a bar chart showing the proportion of participants with hay fever in each gender group.

Would you like to explore a different variable (e.g. age group or BMI) or run a power calculation to see how many participants would be needed to detect this difference?

Statistical test used: (\chi^2) test of independence (2×2 contingency table)

With a p-value above the conventional 0.05 threshold, we do not have statistically significant evidence of a link between gender and self-reported hay fever in this sample.

A bar chart (shown above) illustrates the raw percentages: roughly 41 % of females vs 29 % of males reported hay fever, but the sample size is not large enough for this gap to reach significance.

Possible next steps
• Investigate whether age or BMI confounds this relationship.
• Run a power calculation to estimate the sample size needed to detect the observed difference.
• Examine other respiratory outcomes (e.g., wheeze) by gender.