Q25. Testing for the existence of correlation is equivalent to a. testing for th

Question

Q25. Testing for the existence of correlation is equivalent to
    a. testing for the existence of the slope (1).
    b. testing for the existence of the Y-intercept (0).
    c. the confidence interval estimate for predicting Y.
    d. testing for the existence of the slope (10).

Q26. A real estate builder wishes to determine how house size (House) is influenced by family income (Income), family size (Size), and education of the head of household (School). House size is measured in hundreds of square feet, income is measured in thousands of dollars, and education is in years. The builder randomly selected 50 families and ran the µltiple regression. Microsoft Excel output is provided below:

SUMMARY OUTPUT

Referring to the tables, one individual in the sample had an annual income of $10,000, a family size of 1, and an education of 8 years. This individual owned a home with an area of 1,000 square feet (House = 10.00). What is the residual (in hundreds of square feet) for this data point?
    a. 8.10
    b. 5.40
    c. -5.40
    d. -8.10

Regression Statistics Multiple R 0.865 R Square 0.748 Adjusted R Square 0.726 Standard Error 5.195 Observations 50

Explanation / Answer

Q25. Testing for the existence of correlation is equivalent to
    a. testing for the existence of the slope (1).


Q26:

From the ouput the model is

House-size = -1.6335 + 0.4485 income + 4.2615 *size -0.6517*school

From the given information we have

income = 10, size=1, school = 8

So estimated value of house size is

House-size = -1.6335 + 0.4485 *10 + 4.2615 *1 -0.6517*8 =1.8994 = 1.90 (approx)

So residual is

residual = observed - predicted = 10 - 1.90 = 8.10

Answer : option a

Related Questions

Navigate

• Browse (All)
• Browse Q
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.