A randomly selected group of 100 men and women was studied to see whether there was any difference between the sexes in the incidence of hayfever. Of the 54 men in the sample, 11 reported that they suffered from hayfever. Of the women, only 4 suffered from hayfever. Use a χ2 test to determine whether the incidence of hayfever differs between the sexes. What is the value of χ2 and what is the probability P (two-tailed) that the apparent association could have arise by chance? χ2 = 1.29, P = 0.243 χ2 = 1.02, P = 0.339 χ2 = 1.87, P = 0.164 χ2 = 2.66, P = 0.103 how do i perform this on prism?

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A randomly selected group of 100 men and women was studied to see whether there was any difference between the sexes in the incidence of hayfever. Of the 54 men in the sample, 11 reported that they suffered from hayfever. Of the women, only 4 suffered from hayfever. Use a χ2 test to determine whether the incidence of hayfever differs between the sexes. What is the value of χ2 and what is the probability P (two-tailed) that the apparent association could have arise by chance? χ2 = 1.29, P = 0.243 χ2 = 1.02, P = 0.339 χ2 = 1.87, P = 0.164 χ2 = 2.66, P = 0.103 how do i perform this on prism?

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## Performing a χ2 Test on PrismTo perform a χ2 test on Prism, follow these steps:1. **Open Prism and create a new project.** Start Prism and click on the "New" button to create a new project.2. **Choose the correct table type.** For a χ2 test, you should choose the "Contingency" table type.3. **Enter your data.** In this case, you have two groups (men and women) and two outcomes (hayfever and no hayfever). Your table should look like this: | | Hayfever | No Hayfever | |----------|----------|-------------| | Men | 11 | 43 | | Women | 4 | 46 |4. **Choose the χ2 test.** Click on the "Analyze" button, then choose the "Chi-square test" under the "Contingency table analysis" section.5. **Run the test.** Click on the "OK" button to run the test. Prism will calculate the χ2 value and the P-value for you.The χ2 value tells you how much the observed data deviates from the expected data if there was no association between the groups and the outcomes. The P-value tells you the probability that the observed association could have arisen by chance. If the P-value is less than 0.05, it is usually considered statistically significant.Please note that the exact values of χ2 and P will depend on the specific data you entered. The values you provided (χ2 = 1.29, P = 0.243; χ2 = 1.02, P = 0.339; χ2 = 1.87, P = 0.164; χ2 = 2.66, P = 0.103) are just examples and may not match the results you get from Prism.

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