A data analyst is attempting to understand how ice cream consumption is affected by different attributes. such as cost, temperature. and income level. Which of the following regression analyses…

Question

Options

• ALogistic
• BOrdinary least squares
• CCox
• DPolynomial

• A
  8% (2)
• B
  88% (22)
• D
  4% (1)

Explanation

Ordinary least squares (OLS) is a type of linear regression that is used to fit a regression model that describes the relationship between one or more predictor variables and a numeric response variable. Use when: The relationship between the predictor variable(s) and the response variable is reasonably linear.The response variable is a continuous numeric variable. In this case, the data analyst is interested in understanding how ice cream consumption (the response variable) is affected by different attributes, such as cost, temperature, and income level (the predictor variables). Assuming that these variables have a linear relationship, OLS can be used to estimate the coefficients of the regression equation that best fits the data.OLS can also provide measures of goodness-of-fit, such as R-squared and adjusted R-squared, and test the significance of the coefficients using t-tests and F-tests.

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