Regression Coefficients – Problems, Properties & Solutions

 

Regression Coefficients – Problems, Properties & Solutions

🔹 1️⃣ Meaning of Regression Coefficients

In simple linear regression:

Y=a+byxXY = a + b_{yx}X
  • byxb_{yx} = Regression coefficient of Y on X

  • bxyb_{xy} = Regression coefficient of X on Y

They measure the rate of change of one variable with respect to the other.


🔑 Important Properties of Regression Coefficients

  1. Same Sign Property
    Both byxb_{yx} and bxyb_{xy} have the same sign as correlation (r).

  2. Product Rule

    byxbxy=r2b_{yx} \cdot b_{xy} = r^2
  3. Correlation Relation

    r=±byxbxyr = \pm \sqrt{b_{yx} \cdot b_{xy}}
  4. Independent of Change of Origin
    Regression coefficients do not change if origin changes.

  5. Not Independent of Scale
    They change if scale changes.

  6. If one regression coefficient is greater than 1, the other must be less than 1.


🔢 Problem 1: Find Regression Coefficients

🔹 Given:

  • Xˉ=20\bar{X} = 20

  • Yˉ=30\bar{Y} = 30

  • σX=4\sigma_X = 4

  • σY=5\sigma_Y = 5

  • r=0.6r = 0.6

Find:

  • byxb_{yx}

  • bxyb_{xy}


✅ Solution

Formula:

byx=rσYσXb_{yx} = r \frac{\sigma_Y}{\sigma_X} bxy=rσXσYb_{xy} = r \frac{\sigma_X}{\sigma_Y}

Step 1: Calculate byxb_{yx}

byx=0.6×54b_{yx} = 0.6 \times \frac{5}{4} byx=0.6×1.25b_{yx} = 0.6 \times 1.25 byx=0.75b_{yx} = 0.75

Step 2: Calculate bxyb_{xy}

bxy=0.6×45b_{xy} = 0.6 \times \frac{4}{5} bxy=0.6×0.8b_{xy} = 0.6 \times 0.8 bxy=0.48b_{xy} = 0.48

✅ Check Property

byxbxy=0.75×0.48b_{yx} \cdot b_{xy} = 0.75 \times 0.48 =0.36= 0.36 r2=(0.6)2=0.36r^2 = (0.6)^2 = 0.36

✔ Property Verified


🔢 Problem 2: Find Correlation from Regression Coefficients

🔹 Given:

byx=0.8b_{yx} = 0.8 bxy=0.5b_{xy} = 0.5

Find r.


✅ Solution

r=±byxbxyr = \pm \sqrt{b_{yx} \cdot b_{xy}} r=0.8×0.5r = \sqrt{0.8 \times 0.5} r=0.4r = \sqrt{0.4} r=0.632r = 0.632

Since both coefficients are positive,

r=+0.632r = +0.632

🔢 Problem 3: Find Regression Equations

🔹 Given:

Regression lines:

Y=2X+5Y = 2X + 5 X=0.5Y+1X = 0.5Y + 1

Find:

  • Regression coefficients

  • Correlation coefficient


✅ Step 1: Identify Coefficients

From:

Y=2X+5Y = 2X + 5 byx=2b_{yx} = 2

From:

X=0.5Y+1X = 0.5Y + 1 bxy=0.5b_{xy} = 0.5

✅ Step 2: Find r

r=±2×0.5r = \pm \sqrt{2 \times 0.5} r=1r = \sqrt{1} r=1r = 1

Since both slopes are positive,

r=+1r = +1

✅ Interpretation

Perfect positive correlation.
Both regression lines coincide.


🔢 Problem 4: If One Coefficient > 1

Given:

byx=1.2b_{yx} = 1.2

Find possible value of bxyb_{xy}.


Using Property:

byxbxy=r21b_{yx} \cdot b_{xy} = r^2 \le 1 1.2×bxy11.2 \times b_{xy} \le 1 bxy0.833b_{xy} \le 0.833

So the other coefficient must be less than 1.


📌 Quick Summary Table

ConceptFormula
byxb_{yx}rσYσXr \frac{\sigma_Y}{\sigma_X}
bxyb_{xy}rσXσYr \frac{\sigma_X}{\sigma_Y}
Product rulebyxbxy=r2b_{yx} b_{xy} = r^2
Correlationr=±byxbxyr = \pm \sqrt{b_{yx} b_{xy}}

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