CUET PG PYQs for Regression analysis with Solutions: Practice CUET PG Previous Year Questions

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Sahaj Anand

Content Writer | Journalism Graduate | Updated on - Dec 17, 2025

Regression analysis is an important topic in the Mathematics section in CUET PG exam. Practising this topic will increase your score overall and make your conceptual grip on CUET PG exam stronger.

This article gives you a full set of CUET PG PYQs for Regression analysis with explanations for effective preparation. Practice of CUET PG Mathematics PYQs including Regression analysis questions regularly will improve accuracy, speed, and confidence in the CUET PG 2026 exam.

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CUET PG PYQs for Regression analysis with Solutions

  • 1.
    Given below are two statements:
    Statement I: Line of regression of y on x is the line which gives the best estimate for the value of y for any specified value of x. 
    Statement II: Line of regression of x on y is the line which gives the best estimate for the value of x for any specified value of y. 
    In the light of the above statements, choose the correct answer from the options given below:

      • Both Statement I and Statement II are true
      • Both Statement I and Statement II are false
      • Statement I is true but Statement II is false
      • Statement I is false but Statement II is true

    • 2.
      The term "Residual" is defined as:

        • Fraction of all the test data's variance that is accounted for by the model.
        • The difference between the value predicted for a data point and the actual observed value.
        • A regression method where we tune our model parameters so as to minimize sum of the distances between data points.
        • Actual predicted value.

      • 3.
        The regression analysis confined to the study of only two variables at a time, is called as

          • Simple Regression
          • Difficult Regression
          • Di-Regression
          • Multiple Regression

        • 4.
          In regression analysis independent variable is also called as

            • Explained
            • Regressor
            • Regressed
            • Estimator

          • 5.
            Which of the following is the linear regression equation

              • y=a+bx
              • y=bx2
              • a2+x2=y2
              • ax=y2
            0

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