Answer:
C. Linear regression
Step-by-step explanation:
To determine how much of the variation in scores on a Biology test can be explained or predicted by the number of hours students studied for the test, the appropriate statistical analysis to use is linear regression linear regression is a statistical method used to model the relationship between two variables, where one variable is considered the independent variable (in this case, the number of hours studied) and the other variable is the dependent variable (test scores). By fitting a linear regression model to the data, you can determine the strength and significance of the relationship between the two variables.
Through linear regression analysis, you can estimate the regression equation, which allows you to predict the scores on the Biology test based on the number of hours studied. Additionally, the coefficient of determination (R-squared) can be calculated, which indicates the proportion of the total variation in test scores that can be explained by the number of hours studied.
Therefore, by using linear regression, you can assess the extent to which the variation in scores on the Biology test can be attributed to the number of hours studied by the students.
Answer:
C. Linear regression
Step-by-step explanation:
Linear regression analysis would be used to determine how much of the variation in scores on a Biology test can be explained or predicted by the number of hours the students studied for the test. Specifically, the coefficient of determination (option D) is a measure that quantifies the proportion of the variation in the dependent variable (test scores in this case) that is predictable from the independent variable (hours studied). This analysis helps to understand the strength and direction of the relationship between the two variables.
