Correct Answer: Correct answer is: (C) Linear regression method.
Exam Relevance: GRE, GMAT, PhD Qualifying Exams
Difficulty: Moderate
Concept notes: Linear regression is used to understand the relationship between a dependent variable and one or more independent variables. In this context, it can be used to determine the contribution of a JRF-test score to the overall success of candidates.
Common Mistakes: Students may mistakenly choose correlation methods, thinking they can determine the strength of the relationship without understanding the contribution.
Explanations: Linear regression is the most appropriate method because it allows the researcher to quantify the contribution of the JRF-test score to the overall success of the candidates. By fitting a regression model, the researcher can estimate the coefficients that represent the impact of the JRF-test score on the overall success, thereby understanding its contribution.
Option Analysis: - Option A: F-test is used to compare variances or to test the overall significance of a regression model, but it does not directly measure the contribution of a specific variable.
- Option B: Product-movement correlation measures the strength and direction of the relationship between two variables, but it does not quantify the contribution of one variable to another.
- Option C: Linear regression method is the correct choice as it can quantify the contribution of the JRF-test score to the overall success of the candidates.
- Option D: T-test is used to compare means between two groups, but it does not measure the contribution of a variable to another variable.
Ques 51 explanation is not related to the question…
Very useful question but plz give explanation with correct answer