Regression analysis was applied and the least squares regression line was found to be = 300 + 4x. What would the residual be for an observed value of (3, 309)? -3 3 309 O 312
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- A simple regression model developed for ten pairs of data resulted in a sum of squares of error, SSE = 125. The standard error of the estimate is 12.5 3.5 25 15.6 O 3.95You conducted a regression analysis between the number of absences and number of tasks missed by your 5 classmates in Statistics and Probability. It resulted that the regression line is y = 0.65x + 1.18. What is the predicted number of tasks missed of a learner who is always present? a. The learner has 1 task missed. b. The learner has less than 2 tasks missed. c. The learner has more than 2 tasks missed. d. The learner has no task missed.Based on the null hypothesis when testing the overall model of a multiple regression, which variables are providing significant information about the response? a. all of them b. some of them c. none of them d. most of them
- A real estate analyst has developed a multiple regression line, y = 60 + 0.068 x1 – 2.5 x2, to predict y = the market price of a home (in $1,000s), using independent variables, x1 = the total number of square feet of living space, and x2 = the age of the house in years. The regression coefficient of x2 suggests this: __________. If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homes If the square feet area of living space is kept constant, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted increase of $2500 in the price of the homes Whatever be the square feet area of the living space, a 1 year increase in the age of the homes will result in a predicted drop of $2500 in the price of the homesA regression study was done for 20 cities with latitude and average May temperature as the explanatory variable and response variable respectively. The latitude is ranged from 26 to 47 degrees and the average May temperature is measured in degrees Fahrenheit. Given that the regression equation is ?̂ = 49.4 − 0.313?. (i) Find the proportion of variation that explained by the average May temperature if the total sum of squares and the error sum of squares are 4436.6 and 1185.8 respectively. (ii) By using suitable coefficient(s), comment on the strength of the relationship between the latitude and the average May temperature.A researcher is interested to measure returns to schooling. He ran the regression below: w = a + b*School where w is the hourly wage, 'School' measures years of schooling and b is the coefficient on schooling. Fill in the missing blanks to make the statement correct. Omitting an important variable а. biases b only if it is not related to the 'School' variable. b. does not affect the estimate of b. It only affects the standard error of the estimated coefficient. C. biases b and affects the standard error of the estimated coefficient. d. biases b only if it is related to the 'School' variable.
- For linear regression with one variable, the unpredicted portion of the Y-score variance (MS residual) has df = n - 2. True False Submit AnswerYou’ve run a regression of the effect of years of schooling on wages for a sample of 102,498 individuals. Your regression results are: wage = 2.051 + 0.29 × Years of Schooling (0.0802) (0.0168) Interpret the coefficients from this regression. (The coefficients are shown in the regression equation itself.) The numbers in parentheses under the equation are the standard errors of the estimates for the respective coefficients. Determine whether each coefficient is statistically significant at each of the conventional significance levels. The R2 for this regression is 0.284. Interpret the meaning of this value.A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.
- The money raised and spent (both in millions of dollars) by all congressional campaigns for 8 recent 2-year periods are shown in the table. The equation of the regression line is y = 0.942x +27.609. Find the standard error of estimate s, and interpret the result. 793.9 1042.3 957.7 1203.3 450.7 673.7 745.1 778.6 Money raised, x Money spent, y 734.8 1024.2 929.1 1160.6 448.6 697.9 735.7 751.2 Find the standard error of estimate s, and interpret the result. (Round to three decimal places as needed.) How can the standard error of estimate be interpreted? O A. The standard error of estimate of the money raised for a specific amount of money spent is about s, million dollars. O B. The standard error of estimate of the money spent for a specific amount of money raised is about s, million dollars.A biologist collected data on a sample of 20 porcupines. She wants to be able to predict the body mass of a porcupine (M, in grams) based on the length of the porcupine (L, in cm). Her least squares regression equation is M = – 3089 + 175.6L. Predict the body mass of a porcupine that is 51 cm long. Report your answer using one decimal place. O 5661.0 g O 5732.5 g O 5866.6 g O 6139.2 g eTextbook and Media Save for Later Last saved 3 minutes ago. Attempts: 2 of 3 used Submit Answer Saved work will be auto-submitted on the due date. Auto- submission can take up to 10 minutes.Use the given information to find the coefficient of determination. 31) A regression equation is obtained for a collection of paired data. It is found that the total variation is 24.488, the explained variation is 15.405, and the unexplained variation is 9.083. Find the coefficient of determination.