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Q. Explain Correlation Coefficient?
Ans.
The strength of a linear correlation is determined by how precisely the y variable shifts as the x variable increases. The two pictures on the right show data with a higher correlation than those on the left.
Data is said to have a perfect correlation if all points lie exactly along a line.
The correlation coefficient, r, is a measure of the strength of the correlation. It is a number between 1 and +1. +1 indicates a perfect positive correlation and 1 indicated a perfect negative correlation. If r is positive, then there is a positive correlation between the two variables. If r is negative, there is a negative correlation between the variables.
Q. Explain Linear Regression model? Ans. Linear correlation measures the strength of a linear relationship, but not the exact numerical relationship. Linear regression, o
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Regression line drawn as y=c+1075x, when x was 2, and y was 239, given that y intercept was 11. Caculate the residual
Regression line drawn as Y=C+1075x, when x was 2, and y was 239. Given that y intercept was 11. Calculate the residual
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Data for ogive graph in sectors of indian economy
V ariance A measure of dispersion the variance represents the average distance from any given observation in a series to the mean of that series in the units squared.
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