Practice Linear Regression in Statistics

Use these practice problems to test your method after reviewing the concept explanation and worked examples.

Quick Recap

Linear regression is a statistical method for modeling the relationship between a dependent variable and one or more independent variables by fitting a straight line that minimizes the sum of squared distances from data points to the line (least squares method).

Given scattered points, draw the 'best' line through them. 'Best' means the line that's closest to all points on average. This line lets you predict Y from X.

Showing a random 20 of 50 problems.

Example 1

medium
A regression of ice-cream sales on temperature has slope +2+2 and r=0.9r = 0.9. Does temperature cause sales?

Example 2

medium
You shift all xx values by +10+10 without changing yy. Does the regression slope change?

Example 3

easy
In y^=bx+a\hat{y} = bx + a, what does aa represent?

Example 4

hard
You scale all yy values by 22 but leave xx unchanged. How do slope and intercept of the new regression compare to the old?

Example 5

easy
In y^=4x+11\hat{y} = 4x + 11, by how much does predicted yy change when xx increases by 11?

Example 6

hard
A regression equation is y^=502.3x\hat{y} = 50 - 2.3x. Interpret the slope. If x=8x = 8, find y^\hat{y}.

Example 7

easy
In y^=5x+8\hat{y} = 5x + 8, what is the intercept and what does it mean?

Example 8

medium
Regression line y^=2.5x+4\hat{y}=2.5x+4. The number of hours studied is x and the test score is y^\hat{y}. How much does each extra hour raise the predicted score?

Example 9

easy
In a regression of test score on hours studied, the slope is 55. Interpret it in plain English.

Example 10

easy
Regression line y^=2x+30\hat{y} = -2x + 30. Predict y at x=4x = 4.

Example 11

hard
For data with x=20\sum x = 20, y=60\sum y = 60, xy=250\sum xy = 250, x2=90\sum x^2 = 90, n=5n = 5, find the regression line.

Example 12

challenge
Regression y^=4x+2\hat{y}=4x+2 from data with x from 1 to 6. A student predicts y^\hat{y} at x=6x=6 as 26 and at x=20x=20 as 82. Which prediction is trustworthy and why?

Example 13

medium
Why does a regression equation describe association, not causation?

Example 14

easy
Linear regression fits a line by minimizing what?

Example 15

medium
Regression line y^=7x+50\hat{y} = 7x + 50. Solve for xx when y^=134\hat{y} = 134.

Example 16

easy
Regression line y^=2.5x+4\hat{y} = 2.5x + 4. Find y^\hat{y} at x=0x = 0.

Example 17

medium
A regression slope is b=3b = 3 with sx=4s_x = 4 and sy=20s_y = 20. Find the correlation rr.

Example 18

medium
Data: (xˉ,yˉ)=(5,30)\bar{x},\bar{y}) = (5, 30), sx=2s_x = 2, sy=8s_y = 8, r=0.75r = 0.75. Write the regression equation.

Example 19

hard
Regression residuals are plotted vs. y^\hat{y} and show a clear curved pattern. What does this suggest about the linear model?

Example 20

medium
A regression model of plant height (cm) on water (mL) gives y^=0.1x+4\hat{y} = 0.1x + 4. Interpret slope and intercept in context.