Consider the following regression output: = 0.2033 + 0.656Xt se = (0.0976) (0.1961) r² = 0.397 RSS = 0.0544 ESS = 0.0358 Where: Y = labor force participation rate (LFPR) of women in 1972 and X = LFPR of women in 1968. The regression results were obtained from a sample of 19 cities in the United States.
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- Consider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. Using the 68-95-99.7 rule, between what two values would approximately 95% of the observed responses, y, fall when x = 7?Consider the multiple regression for the following experiment: yi=b0+b1x1i+b2x2i+b3x3i+ei Where yi is the number of touchdowns, x1i is rushing yards, x2i is passing yards, and x3i is the “time of possession of the football” in minutes for that football team. Which of the following statements is true when making an interpretation of the sample slope coefficient? a) a. b2 represents the marginal change in passing yards for every additional touchdown, holding the other variables constant b) b. b2 represents the marginal change in touchdowns for every additional passing yard, holding the other variables constant c) c. b1 represents the marginal change in touchdowns for every additional passing yard, holding the other variables constant d) d. b3 represents the marginal change in touchdowns for every additional minute of time of possession, holding touchdowns constantGiven the partial results from a linear regression model below, a sample size of 504, and ɑ=0.05, What is the F-Statistic for the overall model? Is it statistically significant? What is the R2 for the regression model above?
- Consider the following sample regression equation yˆ = 150 − 20x, where y is the demand for Product A (in 1,000s) and x is the price of the product (in $). The slope coefficient indicates that if _____An investigation into the relationship between an adolescent mother's age x in years and the birth weight y of her baby in grams yielded the regression equation y= - 1163.45 + 245.15x as well as r = .88369, r2= .78091, SSE = 337212.45, and s= 205.30844 1) What is the predicted birth weight for a baby brn to a 17 year old woman? 2) What is the propotion of the variability in the weights of babies born to adolescent mothers that is accounted for by the mother's age? 3) For every additional year in the mother's age that mean birth weight of the baby? (a) increases by about 245g (b) decreases by about 245g (c) increases by about 1163g (d) increases by about 1163g (e) changes by an amount that cannot be determined from the information given.Based on the results of the regression, what would be the mose likely conclusion?
- Jimmy tested a sample with of n=4 pairs of X and Y scores and found SSY = 48 and a Pearson correlation between X and Y of r = 0.4 Calculate whether the Fobserved in this regression experiment is significant at the ∞ = o.01 levelI see that you ran a correlation for Pearson's r, can you run a linear regression?In the following model, "employed" is a dummy indicating a person is employed: donation = B + B edu + Bemployed + uT Running this model will produce the same results of differential in donation between employed people and unemployed people as running two separate regressions for employed people and unemployed people. A. True B. False
- Consider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. The decrease in blood pressure y will vary about this subpopulation mean. What is the distribution of y for this subpopulation?which of the following regressions represents the strongest negative linear relationship between x and y? (Attached in picture provided)Suppose the following data were collected from a sample of 5 car manufacturers relating monthly car sales to the number of dealerships and the quarter of the year. Use statistical software to find the following regression equation: SALESi= b0 + b1DEALERSHIPSi + b2 QUARTER1i+ b3QUARTER2i + b4QUARTER3i+ ei Is there enough evidence to support the claim that on average, car sales are higher in the 4th quarter than in the 2nd quarter at the 0.01 level of significance? If yes, write the regression equation in the spaces provided, rounded to two decimal places. Else, select "There is not enough evidence." Monthly Sales Number of Dealerships 1st Quarter (1 if Jan.-Mar., 0 otherwise) 2nd Quarter (1 if Apr.-Jun., 0 otherwise) 3rd Quarter (1 if Jul.-Sep., 0 otherwise) 4th Quarter (1 if Oct.-Dec., 0 otherwise) 85482 4 1 0 0 0 101319 9 1 0 0 0 121389 12 1 0 0 0 133677 18 1 0 0 0 194588 22 1 0 0 0 82128 4 0 1 0 0 150407 9 0 1 0 0 242714 12 0…