Chapter 16 - Integrated Algebra B

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Chapter 16 - Integrated Algebra B

Algebra U13 HW DAY 10 CORRELATION 1. Below there are six scatter plots, six correlation coefficients, and six terms. Match the appropriate r-value with the scatter plot it most likely corresponds to. Then match the term you think is most appropriate to the r-value as well (not to the graph).

r = 1.0 Weak Negative

r = 0.35 Perfect Positive

r = -0.82 Strong Positive

r = 0 Weak Positive

r = -0.56 Moderate Negative

r = 0.93 No Correlation 2. The scatter plot displays data on the number of defects per 100 cars and a measure of customer satisfaction (on a scale from 1 to 1000, with higher scores indicating greater satisfaction) for the 33 brands of cars sold in the United States in 2009.

Which value below could represent the correlation coefficient for this data set?

(1) r = -0.95 (2) r = -0.24 (3) r = 0.83 (4) r = 1.00

Explain your reasoning for choosing your answer.

3. Which scatterplot below shows the strongest linear relationship? Explain

4. For each of the following residual plots, indicate whether the values would be better represented by a linear or a non-linear relationship. Justify your answer. 5. Which situation describes a correlation that is not a causal relationship?

(1) The length of the edge of a cub and the volume of the cube (2) The distance traveled and the time spent driving (3) The age of a child and the number of siblings that child has (4) The number of classes taught in a school and the number of teachers employed

6. Which statistics would indicate that a linear function would not be a good fit to model a data set?

(1) r = -0.93 (2) r=1 (3) (4)

7. The two-way table below represents clubs that students participate in at school.

What is the marginal relative frequency of the number of males and females that played in the Jazz Band?

(1) 8% (2) 18% (3) 10% (4) 12%

8. The relationship between t, a student’s test scores, and d, the student’s success in college, is modeled by the equation d  0.48t  75.5 . Based on this linear regression model, the correlation coefficient could be (1) Between -1 and 0 (3) equal to -1 (2) Between 0 and 1 (4) equal to 0

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