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bomba923
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Now how exactly did Pearson derive his correlation coefficient?
Pearson Correlation Coefficient: How Did He Derive It?
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In summary, Pearson Correlation Coefficient, also known as Pearson's r, is a statistical measure developed by Karl Pearson in the late 19th century to assess the linear relationship between two continuous variables. It ranges from -1 to +1 and is commonly used in research to identify patterns and trends, make predictions, and evaluate the validity and reliability of data. However, it has limitations such as only measuring linear relationships and being affected by outliers and other factors.
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gimmytang
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Is it simply a definition which reflects the linear relationship between two variables?
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bomba923
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gimmytang said:
That's what it's supposed to do; I'm just wondering how did Pearson derived or came up with the formula for it, which I have in the attached GIF image file, (correlation.gif)
Where x=discrete independent variable, y=discrete dependent variable,
and Sx=standard deviation of x-set, and Sy=standard deviation of y-set
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FAQ: Pearson Correlation Coefficient: How Did He Derive It?
What is Pearson Correlation Coefficient?
Pearson Correlation Coefficient, also known as Pearson's r, is a statistical measure that quantifies the strength and direction of the linear relationship between two continuous variables. It ranges from -1 to +1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and +1 indicates a perfect positive correlation.
Who is the creator of Pearson Correlation Coefficient?
Karl Pearson, a British mathematician and statistician, is credited with developing the Pearson Correlation Coefficient in the late 19th century. He derived this measure as a way to assess the relationship between two continuous variables in a bivariate data set.
How did Karl Pearson derive the Pearson Correlation Coefficient?
Pearson derived the correlation coefficient by using the concept of covariance, which measures how two variables change together, and standard deviation, which measures the spread of data from the mean. He then divided the covariance by the product of the two variables' standard deviations to get the correlation coefficient.
What is the significance of Pearson Correlation Coefficient in research?
Pearson Correlation Coefficient is commonly used in research to determine the strength and direction of the relationship between two continuous variables. It helps researchers identify patterns and trends in data and can be used to make predictions about future outcomes. Additionally, it is useful in determining the validity and reliability of data in a study.
Are there any limitations of Pearson Correlation Coefficient?
Yes, there are some limitations of Pearson Correlation Coefficient. It can only measure linear relationships between variables, meaning that it may not accurately reflect the relationship if the data follows a non-linear pattern. Additionally, it can be influenced by outliers in the data, and it does not account for other factors that may be affecting the relationship between the variables.