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- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?Find the equation of the regression line for the data based on time spend forstudying and current CGPAWe conduct a simple regression of size on hhinc. The regression output is reportedin Table 1. Interpret the sign and magnitude of the estimated coefficients.
- Suppose the following regression equation was generated from the sample data of 50 cities relating number of cigarette packs sold per 1000 residents in one week to tax in dollars on one pack of cigarettes and if smoking is allowed in bars: PACKS, = 59682.369232-1108.267218TAX + 176.926159BARS; + eį. BARS 1 if city i allows smoking in bars and BARS; = 0 if city i does not allow smoking in bars. This equation has an R² value of 0.347972, and the coefficient of BARS, has a P-value of 0.133971. Which of the following conclusions is valid? Answer 2 Points Keypad Keyboard Shortcuts According to the regression equation, cities that allow smoking in bars have lower cigarette sales than cities that do not allow smoking in bars. Regardless of whether or not there is a smoking ban, if a city increases its cigarette tax by one dollar cigarette sales will increase by approximately 1108 packs. ○ If there is no cigarette tax in a city that allows smoking in bars, the approximate number of cigarette…Given: A regression of ln(wage) on educ, exper, exper2, female, married, numdep and two interaction terms female ∗ edu and female ∗ married. (For the interaction terms I multiplied female data x edu data and so forth) Question: What does the coefficient on the interaction term measure? Interpret the coefficients on the interaction term, female ∗ edu and female ∗ married.A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.634 b=30.709 r2=0.948676 r=-0.974 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)
- For each gender, estimate an earnings regression where the dependent variable is Annual Earnings and the independent variable is Age. Report the results for each regression, and provide an interpretation of the coefficient associated with age. Female- annual earning: 49347.58 age: 42.81 education: 14.4 Male- Annual earning: 69984.54 age: 42.86 education: 14.11.A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were: y=ax+b a=-0.634 b=30.709 r2=0.948676 r=-0.974 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý = bo + bịx bo = 36.465 - 1.082 b1 - 0.646 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.711 b=30.651 r²-0.670761 r=-0.819 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)The following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x2 Here SST = 6,871.500, SSR = 6,526.625 , si, = 0.0762, and Si, = 0.0612. a. Compute MSR and MSE (to 3 decimals). MSR MSE = b. Compute F and perform the appropriate F test (to 2 decimals). Use a = 0.05. Use the F table. F The p-value is between 0.025 and 0.05 At a = 0.05, the overall model is not significant c. Perform at test for the significance of B1 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.02 and 0.05 v At a = 0.05, there is not a significant relationship between y and 01. d. Perform a t test for the significance of B2 (to 2 decimals). Use a = 0.05. Use the t table. The p-value is between 0.01 and 0.02 v At a = 0.05, there is not a significant v relationship between y and x2.a) We conduct a regression of size on hhinc, owner, hhsize, hhsize2,and hhsize3. We do not include the constant. The regression output is reported in Table 3. Would you conclude that the home size increases with the household size? Interpret the sign and magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3.
