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Linear Regression Model: Goodness of Fit and Testing of Hypothesis

In: Econometrics in Theory and Practice

Author

Listed:
  • Panchanan Das

    (University of Calcutta, Department of Economics)

Abstract

In a linear regression model, estimation of parameter is done on the basis of a sample randomly taken from the population. As sample is a part of the population, an OLS estimate of a parameter would not be exactly equal to the parameter. So, inference is to be made regarding how a SRF is representative of the PRF. An OLS estimate is a random variable following a probability distribution. Inference about parameters can be done by exploiting the randomness behaviour of statistics. Statistical inference is a process by which one can make inference about unknown population on the basis of the estimates from known sample. In classical econometrics, the principal way of doing this is performing hypothesis tests and constructing confidence intervals. This chapter deals with this problem.

Suggested Citation

  • Panchanan Das, 2026. "Linear Regression Model: Goodness of Fit and Testing of Hypothesis," Springer Texts in Business and Economics, in: Econometrics in Theory and Practice, edition 0, chapter 3, pages 65-94, Springer.
    • Handle: RePEc:spr:sptchp:978-981-95-7226-7_3
    DOI: 10.1007/978-981-95-7226-7_3
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