Linear Regression Review

Front

What is Linear Regression?

Back

Linear Regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

Front

What does a Strong Positive Correlation indicate?

Back

A Strong Positive Correlation indicates that as one variable increases, the other variable also tends to increase, and the points on a scatter plot are closely clustered around a straight line.

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What does a Strong Negative Correlation indicate?

Back

A Strong Negative Correlation indicates that as one variable increases, the other variable tends to decrease, and the points on a scatter plot are closely clustered around a straight line but in a downward slope.

Front

What does No Correlation mean in a scatter plot?

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No Correlation means there is no discernible relationship between the two variables, and the points on the scatter plot are scattered randomly.

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What is the Line of Best Fit?

Back

The Line of Best Fit is a straight line that best represents the data on a scatter plot, minimizing the distance between the line and all the data points.

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How do you calculate the Line of Best Fit?

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The Line of Best Fit can be calculated using the least squares method, which minimizes the sum of the squares of the vertical distances of the points from the line.

Front

What is the formula for a linear equation?

Back

The formula for a linear equation is typically written as y = mx + b, where m is the slope and b is the y-intercept.

Front

What does the slope (m) represent in a linear equation?

Back

The slope (m) represents the rate of change of the dependent variable (y) with respect to the independent variable (x). It indicates how much y changes for a one-unit increase in x.

Front

What does the y-intercept (b) represent in a linear equation?

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The y-intercept (b) represents the value of the dependent variable (y) when the independent variable (x) is zero.

Front

What is a scatter plot?

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A scatter plot is a graphical representation of two variables, where each point represents an observation in the dataset, allowing for visual assessment of relationships.