The following equation is an estimated regression equation, given in the form Y-

Question

The following equation is an estimated regression equation, given in the form Y-hat- ßo- hat + 1-hati, or what your book calls y-hat = a bx. It is based on data for 55 rural Indian households Y-hati = 94.21 + 0.44Xi where Y is weekly household Expenditures on Food, measured so that 1-1 rupee etc X is weekly household Total Expenditures, also measured so that 1-1 rupee Below is some information provided by the computer program that estimated this equation Answer the following questions for the equation. Standard ror 50.8563 0.0783 Variable Parameter Estimate 94.2087 Sig./Prob 1.85 5.58 0.07 0.0000 Intercept/Const otalExpend r' = 0.3698 Note: N= 55 Source: Gujarati and Porter (2009), various pages including 133 0.4368 What is the estimated intercept? [1 point] a. b. What is the estimated slope? [1 point] c. Interpret the estimated slope, translating the numbers into words that have meaning. [3 points] How does the computer come up with the t-value of 5.58? Show work. [2 points] When do we observe a negative t-value in regression output? [1 point] Is the estimated slope statistically significant? Explain clearly how you decide. [2 points] Is the estimated slope substantively significant? Briefly explain. [2 points] Produce a confidence interval for the parameter estimate for "TotalExpend."2 points] d. e. f. g. h. i. Predict the expected Expenditure on Food for a household whose Total j. Expenditure is 200 rupees. [2 points] Consider the r2 for this equation. What does this mean? [2 points] 2. Define a spurious X-Y relationship. Given an example of a seeming X-Y relationship that might be spurious and why

Explanation / Answer

We are allowed to do 4 subparts question at a time. Post again for more subparts of question.

a) Intercept = 94.2087

b) Slope = 0.4368

c) Slope 0.4368 tells that if total expenditures increase by 1 rupee, expenditure on rupee increases by 0.4368 rupees.

d) t = Slope/standard error

t = 0.4368/0.0783 = 5.5785

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