Linear Regression

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What is Linear Regression?

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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.

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What does the equation of a line in linear regression look like?

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The equation of a line in linear regression is typically written as y = mx + b, where m is the slope and b is the y-intercept.

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What is the slope in a linear regression equation?

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The slope (m) indicates the rate of change of the dependent variable (y) for each unit change in the independent variable (x).

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What is the y-intercept in a linear regression equation?

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

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What is a line of best fit?

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A 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 data points.

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What does a positive correlation indicate in a scatterplot?

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A positive correlation indicates that as one variable increases, the other variable also tends to increase.

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What does a negative correlation indicate in a scatterplot?

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A negative correlation indicates that as one variable increases, the other variable tends to decrease.

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What is the purpose of calculating a linear regression equation?

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The purpose of calculating a linear regression equation is to predict the value of the dependent variable based on the value of the independent variable.

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What is the difference between correlation and causation?

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Correlation indicates a relationship between two variables, while causation indicates that one variable directly affects the other.

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What is a scatterplot?

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A scatterplot is a graph that displays values for two variables for a set of data, showing how much one variable is affected by another.