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DY0-001 · Question #46

A data scientist is building an inferential model with a single predictor variable. A scatter plot of the independent variable against the real-number dependent variable shows a strong relationship…

The correct answer is C. A linear regression. You have a continuous real-valued outcome, a single normally distributed predictor, and a roughly linear relationship on the scatter plot. Linear regression directly models that relationship with an easy-to-interpret slope and intercept, making it the best choice.

Modeling, Analysis, and Outcomes

Question

A data scientist is building an inferential model with a single predictor variable. A scatter plot of the independent variable against the real-number dependent variable shows a strong relationship between them. The predictor variable is normally distributed with very few outliers. Which of the following algorithms is the best fit for this model, given the data scientist wants the model to be easily interpreted?

Options

  • AA logistic regression
  • BAn exponential regression
  • CA linear regression
  • DA probit regression

How the community answered

(22 responses)
  • A
    5% (1)
  • B
    9% (2)
  • C
    82% (18)
  • D
    5% (1)

Explanation

You have a continuous real-valued outcome, a single normally distributed predictor, and a roughly linear relationship on the scatter plot. Linear regression directly models that relationship with an easy-to-interpret slope and intercept, making it the best choice.

Topics

#linear regression#model interpretability#inferential modeling#predictor variables

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