Using empirical data, a researcher developed a linear regression model of Ỹ = 65 + 0.9x1 – 0.5x2 %3D to predict Y, the life span in years, where x, is the average hours per week of exercise and x2 is the number of years spent smoking. Using this model, what is the predicted life span for a person who exercised an average of 5 hours per week and smoked for 20 years? 50.5 years 59.5 years O 65 years 80.5 years

You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are:      I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars.         Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.

In a simple linear regression equation, X is the----- variable.

also compute the regression equation in which you predict Y using X as the predictor variable

Suppose you ran a regression of AGE predicting INCOME (thousands of dollars). If your estimated line was INCOME = -1.5 + 1.2*AGE + ε, how much more income do you expect to make for every two years you age? (Express your answer in thousands of dollars.)

The y-intercept in a linear regression model is always relevant and of interest to investigators for every model constructed.  True  False

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 homes

Define linear regression?

A biologist wants to predict the height of male giraffes, y, in feet, given their age, x1, in years, weight, x2, in pounds, and neck length, x3, in feet. She obtains the multiple regression equation yˆ=7.36+0.00895x1+0.000426x2+0.913x3. Predict the height of a 12-year-old giraffe that weighs 3,100 pounds and has a 7-foot-long neck, rounding to the nearest foot.

The mall has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents(Y). Analysis on the set finds that the regression equation is Y=100-3X. What is the likely number of accidents for someone aged 30?     97     100     10     none of the above