{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

# exam2_sp07_stu_answers - Name_Solution Problem#1(20 points...

This preview shows pages 1–2. Sign up to view the full content.

Name: ___________________ Solution ______________ Problem #1 (20 points total) A company is evaluating the ultimate strength (Su) of two types of cement as it cures over time. Consider the raw data, the best-fit lines, and the r-squared values determined using the method of least-squares for Cement A (A) and Cement B (B) below. Su = 0.0386*Time + 2.0571 0 1 2 3 4 0 1 2 3 4 5 6 Curing Time (h) Ultimate Strength, Su (GPa) Su = 0.6671*Time + 0.5821 0 1 2 3 4 0 1 2 3 4 5 6 Curing Time (h) Ultimate Strength, Su (GPa) Cement A: 2 2.25 and 0.388 Su r = = Cement B: 2 2.25 and 0.949 Su r = = 1.1 (4 points) The computed r-squared value for A is much less than that of B because: (Clearly circle one response.) a. The Sum of Squares of Errors (SSE) for A is considerably less than for B b. The Sum of Squares of Errors (SSE) for A is considerably greater than for B c. The Sum of Squares of Deviations (SST) for A is considerably less than for B d. The Sum of Squares of Deviations (SST) for A is considerably greater than for B e. Both B and C 1.2 (8 points) Which of the following statements is/are true? (Circle all that are true.) a. The slope of the regression line for B is greater than the slope of the regression line for A. b. The “goodness of fit” (as measured by r 2 ) of the regression line for B is greater than “goodness of fit” of the regression line for A. c. The value of intercept of the regression line for A is greater than the value of the intercept of the regression line for B. d. The mean Su value for A is equal to the mean Su value for B. 1.3 (4 points) The intercept for Cement B is: (Clearly circle one response) a. 0.75 b. 0.5821 c. 0.6671 d. 0 1.4 (2 points) The r 2 value of B is 0.949. This means that 94.9% of the variation of the data around the regression line is due to unexplained error. (Clearly circle one response) True False 1.5 (2 points) By comparing A and B, we can tell that the regression line for A fits the data for A

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 6

exam2_sp07_stu_answers - Name_Solution Problem#1(20 points...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online