Concept explainers
In Problem 14.5 on page 542, you used alcohol percentage and chlorides to predict wine quality (stored in VinhoVerde). Using the results from that problem,
a. at the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these results, indicate the most appropriate regression model for this set of data.
b. compute the coefficients of partial determination,
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Basic Business Statistics, Student Value Edition
- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardA set of X and Y scores has SSX = 5, SSY = 7.5, and SP = 15. The regression equation for these scores will have a slope constant of 2. true or false?arrow_forwardIn a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it means that the relationship between X1 and Y is significant the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, holding X2 constant. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without regard to X2 the estimated mean of Y is 2 when X1 equals zero.arrow_forward
- ) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression: Multiple R 0.4145 R Square 0.1718 Adjusted R Square 0.1600 SEE 92.3760 Conduct a test at the level to see if conditional heteroskedasticity is present In view of your answer for a), what needs to be done?arrow_forwardIn estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression: Multiple R 0.4145 R Square 0.1718 Adjusted R Square 0.1600 SEE 92.3760 Conduct a test at the level to see if conditional heteroskedasticity is presentarrow_forwardThe managing director of a company wants to find whether there is a relationship between units of a product produced and the profits in a period of 12 months. Month Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec Units produced (X)‘000 2 3 5 8 11 10 12 15 17 18 20 24 Profits (Y) ‘000 3 5 8 11 13 14 16 20 22 24 26 30 i. Calculate the regression equation of the form Y = a + bX and hence estimate the value of the profits when 25,000 units are produced. ii. Calculate the regression equation of the form X = a + bY and hence estimate the value of the units produced when 27,000 in profits is made. iii. Calculate and both the Pearson correlation coefficient and coefficient of determination, interpret both and justify in this case why it would be prudent to rely on the coefficient of determination rather than Pearson in decision…arrow_forward
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.9 8.4 6.6 3.8 2.6 2.3 2.2 0.9 y 14.2 11.1 9.6 7 6.2 6.1 5.8 5 x = thousands of automatic weaponsy = murders per 100,000 residentsThis data can be modeled by the equation y=0.85x+4.03. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 7.7 thousand automatic weapons?arrow_forwardhe following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 60 30 1995 130 40 100 50 2000 330 130 280 140 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a)With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) = Use technology to obtain the coefficient of correlation r. (Round your answer to three decimal places.) r =arrow_forwardA surgery intern has conducted a study of the sleeping habits of her colleagues and has developed a following regression equation: y-hat = 6 + 0.1X, where X is the number of hours working on one shift, and Y is the number of hours sleeping at night after that shift. Yvette worked 10 hours and slept 8 hours. What is Yvette’s residual? 0.1 1 6 7arrow_forward
- The following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 60 30 1995 130 40 120 50 2000 330 130 280 140 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a) With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) = Graph the associated points and regression line. (b) What does the slope tell you about the relationship between the number of social science doctorates and the number of education doctorates? The slope tells us the increase in the number of education doctorates for each additional social science doctorate.The slope tells us the decrease in the number of education doctorates for each additional social science doctorate. The slope tells us the increase in the number…arrow_forwardIf the equation of the regression line that relates hours per week spent in the tutor lab, x, to GPA, y, is y=2.1+0.28, then the best presdiction for the GPA of students who never go into the lab would be 2.1 True Or Falsearrow_forwardThe following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 70 30 1995 130 40 110 50 2000 330 130 280 140 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a) With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) = Graph the associated points and regression line. (b) What does the slope tell you about the relationship between the number of social science doctorates and the number of education doctorates? The slope tells us the increase in the number of social science doctorates for each additional education doctorate.The slope tells us the increase in the number of education doctorates for each additional social science doctorate. The slope tells us the decrease in the number…arrow_forward
- Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning