Multiple Linear Regression: Quick Guide with Examples
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Questions and Answers

What is the purpose of multiple linear regression?

  • To estimate the relationship between one independent variable and one dependent variable
  • To estimate the relationship between multiple dependent variables
  • To estimate the relationship between two or more independent variables and one dependent variable (correct)
  • To estimate the relationship between two dependent variables and one independent variable

    • Which assumption is important to check before developing a multiple linear regression model?

  • Correlation between dependent variables (correct)
  • Homogeneity of variance
  • Independence of observations
  • Normality of data distribution

    • What does homoscedasticity refer to in the context of multiple linear regression?

  • The data follows a normal distribution
  • There are no hidden relationships among variables
  • The size of the error in prediction doesn’t change significantly across the values of the independent variable (correct)
  • The observations in the dataset were collected using statistically valid sampling methods

    • What happens if two independent variables in a multiple linear regression model are too highly correlated?

    <p>Only one of them should be used in the regression model</p> Signup and view all the answers

    What type of distribution does the data need to follow for multiple linear regression?

    <p>Normal distribution</p> Signup and view all the answers

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