Revision of Linear and Quadratic Regression

What is the main objective of simple linear regression?

• To calculate the mean of the variables

• To establish a linear relationship between variables for prediction.

In simple linear regression, what is the role of the independent variable?

• The independent variable is irrelevant in simple linear regression

• The role of the independent variable is to predict or explain the dependent variable.

What does the coefficient of determination (R-squared) represent in simple linear regression?

• How well the model fits the data points. The closer to 1, the better.

• Amount of error in the model predictions

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What is the difference between correlation and regression in simple linear regression?

• Correlation measures the strength and direction of a linear relationship, while regression estimates the equation of the line.

• Correlation is always positive, while regression can be negative.

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What is the significance of the y-intercept in simple linear regression?

• The intercept is the slope of the regression line

• The intercept represents the value of the dependent variable when all independent variables are zero.

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How can outliers affect the results of simple linear regression?

• Outliers have no impact on simple linear regression

• Outliers can skew the line of best fit, affecting the overall accuracy and reliability of the regression model.

The turning point of the parabola is called the

• vertex

• solutions

The equation of the parabola that best fits a set of data is called

• quadratic formula

• quadratic regression

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The point(s) in the graph that passes through the x-axis are called the

• x-Intercepts

• y-Intercept

The point in the graph that passes through the y-axis

• y-Intercept

• Standard Form