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Karl Person's Coefficient of Correlation - Business Mathematics & Statistics Video Lecture | Business Mathematics and Statistics - B Com

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FAQs on Karl Person's Coefficient of Correlation - Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com

1. What is Karl Pearson's coefficient of correlation?
Ans. Karl Pearson's coefficient of correlation, also known as Pearson's correlation coefficient, is a statistical measure that measures the strength and direction of the linear relationship between two variables. It is denoted by the symbol "r" and ranges from -1 to +1. A positive value indicates a positive linear relationship, a negative value indicates a negative linear relationship, and a value close to 0 indicates no linear relationship.
2. How is Karl Pearson's coefficient of correlation calculated?
Ans. To calculate Karl Pearson's coefficient of correlation, the following steps are followed: 1. Calculate the mean (average) of both variables. 2. Calculate the difference between each data point and its respective mean for both variables. 3. Multiply the differences obtained in step 2 for each data point and sum them up. 4. Square the differences obtained in step 2 for each data point, sum them up, and find the square root. 5. Divide the sum obtained in step 3 by the product of the values obtained in steps 4 for both variables. 6. The result obtained is the value of Karl Pearson's coefficient of correlation (r).
3. What does a correlation coefficient of 0.8 indicate?
Ans. A correlation coefficient of 0.8 indicates a strong positive linear relationship between two variables. This means that as one variable increases, the other variable tends to increase as well. The closer the correlation coefficient is to 1, the stronger the relationship. In this case, 80% of the variability in one variable can be explained by the other variable.
4. Can Karl Pearson's coefficient of correlation be negative?
Ans. Yes, Karl Pearson's coefficient of correlation can be negative. A negative correlation coefficient indicates a negative linear relationship between two variables. This means that as one variable increases, the other variable tends to decrease. The closer the correlation coefficient is to -1, the stronger the negative relationship. In this case, 80% of the variability in one variable can be explained by the other variable, but in the opposite direction.
5. What are the limitations of Karl Pearson's coefficient of correlation?
Ans. Some limitations of Karl Pearson's coefficient of correlation include: 1. It only measures the strength and direction of linear relationships and may not capture non-linear relationships. 2. It is sensitive to outliers, meaning that extreme values can significantly affect the correlation coefficient. 3. It assumes that the relationship between variables is constant throughout the entire data range. 4. It only measures the association between two variables and does not imply causation. 5. It may not be appropriate to use when the data is not normally distributed or when there are violations of other underlying assumptions.
115 videos|142 docs
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