
AP Stats-Linear Regression
Authored by Gina Vifquain
Mathematics
11th - 12th Grade
CCSS covered
Used 94+ times

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About
This quiz focuses on linear regression analysis within the broader context of AP Statistics, targeting students at the advanced high school level (grades 11-12). The questions comprehensively assess students' understanding of correlation coefficients, including their proper range and interpretation from scatter plots, residual calculations and analysis, least squares regression line equations, and the coefficient of determination (R²). Students must demonstrate mastery of interpreting slope and y-intercept in contextual situations, reading and analyzing scatter plots to determine residual signs, and distinguishing between correlation and causation concepts. The mathematical reasoning required includes understanding that correlation coefficients range from -1 to 1, recognizing that residuals represent the difference between actual and predicted values, and interpreting regression parameters within real-world contexts such as hamster growth patterns and income predictions based on education levels. Created by Gina Vifquain, a Mathematics teacher in the US who teaches grades 11 and 12. This quiz serves as an excellent formative assessment tool for AP Statistics students working through their linear regression unit, providing immediate feedback on conceptual understanding before high-stakes testing. Teachers can deploy this as a warm-up activity to gauge student readiness for more complex regression topics, assign it as homework to reinforce classroom instruction, or use it as a review session before unit exams. The variety of question types—from visual interpretation to contextual analysis—makes it particularly valuable for identifying specific areas where students need additional support. This assessment aligns with Common Core standards S-ID.B.6 (representing data on two quantitative variables and summarizing relationships) and AP Statistics Learning Objectives covering bivariate data analysis, correlation, and linear regression modeling.
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Estimate the correlation coefficient from the graph shown.
r = -0.956
r = 0.956
r = -0.438
r = 0
Tags
CCSS.HSS.ID.B.6
CCSS.HSS.ID.C.8
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which of the following could be true?
Tags
CCSS.HSF.LE.B.5
3.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is the value of the correlation coefficient, r?
Tags
CCSS.HSS.ID.B.6
CCSS.HSS.ID.C.8
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How do you calculate a residual?
Actual - Predicted
Predicted - Actual
Take the square root of R2
Multiply r by sy and divide by sx
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The scatter plot shows the relationship between the number of chapters and the total number of pages for several books. The residual for 12 chapters would be ______.
positive
negative
zero
impossible to determine from this graph
Tags
CCSS.8.EE.C.8C
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Write the linear regression equation for the data set foot length (x) and height (y).
Tags
CCSS.HSF.LE.B.5
7.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
Some data was collected on the weight of a hamster for the first 25 weeks after its birth. The linear regression equation is: Weight = 100 + 40(Time). Which is the best description of the slope for this regression equation in context of the problem?
The slope tells us that hamsters will gain 100 pounds per week.
The slope is 40 grams/week which means the hamster is predicted to gain weight at this rate.
The slope is 40 and it means the hamsters are predicted to gain 1 pound every 40 weeks.
The slope is 100, which is the weight at birth.
Tags
CCSS.HSS.ID.C.7
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