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Obtain two regression equations by the method of least square from the following data : x : 8 6 4 7 5 y : 9 8 5 6 2?
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Obtain two regression equations by the method of least square from the...
Regression Equations by the Method of Least Squares


Data:


  • x: 8 6 4 7 5

  • y: 9 8 5 6 2



Explanation:

Regression analysis is used to determine the relationship between a dependent variable and one or more independent variables. The method of least squares is a statistical technique used to find the line of best fit for a set of data. In this method, the sum of the squares of the vertical distances between each data point and the line of best fit is minimized.


Regression Equation for y on x:

The regression equation for y on x is used to predict the value of y for a given value of x. It is represented as:

y = a + bx


  • a: y-intercept

  • b: slope of the line



Step 1: Calculate the mean of x and y


  • Mean of x = (8+6+4+7+5)/5 = 6

  • Mean of y = (9+8+5+6+2)/5 = 6



Step 2: Calculate the slope (b)

b = Σ[(x - x̄)(y - ȳ)] / Σ[(x - x̄)²]


  • Σ[(x - x̄)(y - ȳ)] = (8-6)(9-6) + (6-6)(8-6) + (4-6)(5-6) + (7-6)(6-6) + (5-6)(2-6) = -2+0-2+0-4 = -8

  • Σ[(x - x̄)²] = (8-6)² + (6-6)² + (4-6)² + (7-6)² + (5-6)² = 4+0+4+1+1 = 10

  • b = -8/10 = -0.8



Step 3: Calculate the y-intercept (a)

a = ȳ - bx̄


  • a = 6 - (-0.8)(6) = 10.8



Step 4: Write the regression equation for y on x

y = 10.8 - 0.8x


Regression Equation for x on y:

The regression equation for x on y is used to predict the value of x for a given value of y. It is represented as:

x = a' + b'y


  • a': x-intercept

  • b': slope of the line



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Obtain two regression equations by the method of least square from the following data : x : 8 6 4 7 5 y : 9 8 5 6 2?
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