A Level Psychology OCR Practice Exam

Which factor is crucial for calculating degrees of freedom in statistical tests?

1. Number of variables

2. Sample size minus one

3. Row and column counts

4. Standard deviation

The correct answer is: Row and column counts

The calculation of degrees of freedom in statistical tests is fundamentally related to the structure of the data being analyzed, specifically the number of independent categories pertaining to the sample size and the number of parameters being estimated. In most common statistical tests, such as t-tests or ANOVA, degrees of freedom typically depend on the sample size and the number of groups or categories that are being compared. For example, in a t-test comparing two means, the degrees of freedom are determined by taking the total sample size of the two groups minus the number of groups. This leads to a formula where the degrees of freedom reflect how many values can vary independently while still satisfying the constraints of the analysis. While aspects like the number of variables or the standard deviation are important in other contexts, they do not directly determine the degrees of freedom for the majority of statistical tests. The correct choice highlights the importance of understanding the relationship between the structure of the data and how that influences the calculation of degrees of freedom, particularly in relation to the arrangements of rows and columns in contingency tables or when dealing with multivariate data.