Data Science Classroom Series – 25/Nov/2021

Reading the Regression Analysis

  • Lets look at one more sample data and try to read the Regression Analysis Summary. Refer Here for the dataset

  • The Summary which we got is as shown below Preview

  • What we really want?

    • Regression equation:
      • y-hat = 528.06717 + 14.833x
    • Significance
    • Explanatory power
  • Regression Statistics Preview

  • ANOVA: Preview Preview

  • Multiple R: This is absolute value of teh correlation coeffecient of two variables (X and Y)

  • Standard error: This is measure of precision of the model

  • R-squared = measures how much of total variability is explained by your model

  • Adjusted R-squared is the modified version of R-squared that has been adjust for number of predictors in the model

    • Multivariate Regressions are always better than univariate, as with each additonal value you add the explanatory power may increase or stay the same
  • F-Statistic: This tests the overall significance of the model

    • H0 : b1 = b2 = b3...bk=0
    • H1: at least one of b(i) !=0

Multiple Linear Regression model

  • So far in Single linear regression Preview
  • So in multiple linear regression Preview

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