What Linear association is
Linear association is a type of statistical relationship between two variables that can be described using a straight line. It is also known as linear correlation and is used to measure the strength of the relationship between two variables.
Steps for Linear Association:
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Collect data: The first step in finding a linear association is to collect data. This data should include two variables that you want to analyze.
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Plot the data: After collecting the data, plot the data on a graph. This will provide a visual representation of the linear association between the two variables.
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Calculate the correlation coefficient: The next step is to calculate the correlation coefficient. This is a numerical measure of the strength of the linear association between the two variables.
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Interpret the correlation coefficient: Once the correlation coefficient has been calculated, it can be interpreted. A correlation coefficient of 1 indicates a perfect linear association, while a correlation coefficient of 0 indicates no linear association. Values between 0 and 1 indicate a weak to strong linear association.
Examples
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Linear regression can be used to analyze the relationship between two continuous variables, such as height and weight.
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Linear regression can be used to analyze the relationship between a single continuous variable and a categorical variable, such as salary and job title.
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Linear regression can be used to analyze the relationship between a continuous dependent variable and a set of independent variables, such as housing prices and square footage, number of bedrooms, and number of bathrooms.