Which term describes a statistical method that evaluates how closely observed data matches expected outcomes?

• A. Chi-squared test
• B. Standard error
• C. Confidence interval
• D. Statistical correlation

Answer: (A)

The term that describes a statistical method to evaluate how closely observed data matches expected outcomes is the Chi-squared test. This test is particularly useful in determining whether there is a significant difference between the expected frequencies and the observed frequencies in categorical data.

In the context of genetics, for example, the Chi-squared test can be applied to analyze the distribution of phenotypes in offspring versus what would be expected based on Mendelian inheritance patterns. By calculating the Chi-squared statistic, researchers can assess whether deviations from the expected ratios could be attributed to random chance or to other factors such as selection or linkage.

The Chi-squared test provides a p-value which indicates the probability of observing data at least as extreme as the collected data, given that the null hypothesis (which usually assumes no effect or no difference) is true. A low p-value suggests that the observed and expected outcomes are significantly different, leading to a rejection of the null hypothesis.

The other terms have different applications: standard error measures how much sample mean estimates vary from the actual population mean, while confidence intervals provide a range of values that likely contain the population mean based on sample data. Statistical correlation indicates the degree to which two variables move in relation to each other but does not directly assess observed versus