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तमिलनाडु बोर्ड ऑफ सेकेंडरी एज्युकेशनएचएससी वाणिज्य कक्षा ११

The lines of regression intersect at the point

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प्रश्न

The lines of regression intersect at the point

विकल्प

  • (X, Y)

  • `(bar"X", bar"Y")`

  • (0, 0)

  • x, σy)

MCQ
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उत्तर

`(bar"X", bar"Y")`

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Regression Analysis
  क्या इस प्रश्न या उत्तर में कोई त्रुटि है?
अध्याय 9: Correlation and Regression Analysis - Exercise 9.3 [पृष्ठ २२९]

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सामाचीर कलवी Business Mathematics and Statistics [English] Class 11 TN Board
अध्याय 9 Correlation and Regression Analysis
Exercise 9.3 | Q 21 | पृष्ठ २२९

संबंधित प्रश्न

Given the following data, what will be the possible yield when the rainfall is 29.

Details Rainfall Production
Mean 25`` 40 units per acre
Standard Deviation 3`` 6 units per acre

Coefficient of correlation between rainfall and production is 0.8.


The following data relate to advertisement expenditure (in lakh of rupees) and their corresponding sales (in crores of rupees)

Advertisement expenditure 40 50 38 60 65 50 35
Sales 38 60 55 70 60 48 30

Estimate the sales corresponding to advertising expenditure of ₹ 30 lakh.


For 5 observations of pairs of (X, Y) of variables X and Y the following results are obtained. ∑X = 15, ∑Y = 25, ∑X2 = 55, ∑Y2 = 135, ∑XY = 83. Find the equation of the lines of regression and estimate the values of X and Y if Y = 8; X = 12.


The two regression lines were found to be 4X – 5Y + 33 = 0 and 20X – 9Y – 107 = 0. Find the mean values and coefficient of correlation between X and Y.


The regression coefficient of X on Y


The regression coefficient of Y on X


If X and Y are two variates, there can be at most


The lines of regression of X on Y estimates


X and Y are a pair of correlated variables. Ten observations of their values (X, Y) have the following results. ∑X = 55, ∑XY = 350, ∑X2 = 385, ∑Y = 55, Predict the value of y when the value of X is 6.


The following information is given.

Details X (in ₹) Y (in ₹)
Arithmetic Mean 6 8
Standard Deviation 5 `40/3`

Coefficient of correlation between X and Y is `8/15`. Find

  1. The regression Coefficient of Y on X
  2. The most likely value of Y when X = ₹ 100.

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