[amp_mcq option1=”(A) and (R) are correct” option2=”(A) is correct, but (R) is not correct” option3=”(A) is not correct, but (R) is correct” option4=”Both (A) and (R) are not correct” correct=”option2″]<\/p>\n
The correct answer is: B. (A) is correct, but (R) is not correct<\/strong><\/p>\n Assertion (A) is correct. The regression coefficient of X on Y is the slope of the line that best fits the data when X is the independent variable and Y is the dependent variable. If the regression coefficient of X on Y is greater than one, then the line slopes upwards from left to right, which means that as X increases, Y also increases. This implies that there is a positive correlation between X and Y.<\/p>\n Reason (R) is not correct. The geometric mean between two regression coefficients is not the coefficient of correlation. The coefficient of correlation is a measure of the strength of the linear relationship between two variables. It is calculated by taking the square root of the product of the two regression coefficients.<\/p>\n Here is an example to illustrate why assertion (A) is correct but reason (R) is not correct. Consider the following data:<\/p>\n X | Y The regression coefficient of X on Y is 2. This means that the line that best fits the data has a slope of 2. The regression coefficient of Y on X is 1. This means that the line that best fits the data has a slope of 1. The geometric mean of the two regression coefficients is $\\sqrt{2 \\times 1} = \\sqrt{2}$. The coefficient of correlation is $\\frac{2 \\times 1}{\\sqrt{2 \\times 2}} = \\frac{2}{\\sqrt{4}} = \\frac{1}{\\sqrt{2}}$.<\/p>\n As you can see, the geometric mean of the two regression coefficients is not equal to the coefficient of correlation.<\/p>\n","protected":false},"excerpt":{"rendered":" [amp_mcq option1=”(A) and (R) are correct” option2=”(A) is correct, but (R) is not correct” option3=”(A) is not correct, but (R) is correct” option4=”Both (A) and (R) are not correct” correct=”option2″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[701],"tags":[],"class_list":["post-33797","post","type-post","status-publish","format-standard","hentry","category-business-statistics-and-research-methods","no-featured-image-padding"],"yoast_head":"\n
\n——- | ——–
\n1 | 2
\n2 | 4
\n3 | 6
\n4 | 8<\/p>\n