Which statement correctly lists the common statistical tests for means and proportions in dental studies?

Which statement correctly lists the common statistical tests for means and proportions in dental studies?

• A. Means: t-test and ANOVA; Proportions: chi-square and Fisher's exact test.
• B. Means: ANOVA only; Proportions: z-test.
• C. Means: regression analysis; Proportions: ANOVA.
• D. Means: chi-square; Proportions: Fisher's exact test.

Answer: (A)

When you’re evaluating outcomes in dental studies, match the test to the type of data you have. For continuous measurements that reflect a mean (like mean probing depth, mean tooth mobility, or mean caries score), you compare averages using tests designed for means: a t-test for comparing two groups, and ANOVA when you’re comparing three or more groups. These tests focus on whether the average values differ across groups and are based on the distribution of the data and variance assumptions. For categorical outcomes that are summarized as proportions (like the proportion of patients with a filled tooth, treatment success rate, or presence vs. absence of a condition), you compare proportions with tests designed for categorical data. The chi-square test is common for evaluating whether observed proportions differ across groups in larger samples, while Fisher’s exact test is used when sample sizes are small or expected counts are low and an exact calculation is preferred. Other options either rely on different contexts (like regression, which is for modeling relationships rather than simple group comparisons) or mix data types (such as using a chi-square for means). The pairing of t-test/ANOVA for means and chi-square/Fisher’s exact for proportions best fits typical dental study designs and data types.

When you’re evaluating outcomes in dental studies, match the test to the type of data you have. For continuous measurements that reflect a mean (like mean probing depth, mean tooth mobility, or mean caries score), you compare averages using tests designed for means: a t-test for comparing two groups, and ANOVA when you’re comparing three or more groups. These tests focus on whether the average values differ across groups and are based on the distribution of the data and variance assumptions.

For categorical outcomes that are summarized as proportions (like the proportion of patients with a filled tooth, treatment success rate, or presence vs. absence of a condition), you compare proportions with tests designed for categorical data. The chi-square test is common for evaluating whether observed proportions differ across groups in larger samples, while Fisher’s exact test is used when sample sizes are small or expected counts are low and an exact calculation is preferred.

Other options either rely on different contexts (like regression, which is for modeling relationships rather than simple group comparisons) or mix data types (such as using a chi-square for means). The pairing of t-test/ANOVA for means and chi-square/Fisher’s exact for proportions best fits typical dental study designs and data types.