(a) Develop an estimated regression equation relating y to x,. (Round your numerical values to one decimal place.) シ= Predict y if x, = 44. (Round your answer to one decimal place.) (b) Develop an estimated regression equation relating y to x,. (Round your numerical values to one decimal place.) ý = Predict y if x, = 14. (Round your answer to one decimal place.) (c) Develop an estimated regression equation relating y to x, and x,. (Round your numerical values to one decimal place.) II

(a) Develop an estimated regression equation relating y to x,. (Round your numerical values to one decimal place.) シ= Predict y if x, = 44. (Round your answer to one decimal place.) (b) Develop an estimated regression equation relating y to x,. (Round your numerical values to one decimal place.) ý = Predict y if x, = 14. (Round your answer to one decimal place.) (c) Develop an estimated regression equation relating y to x, and x,. (Round your numerical values to one decimal place.) II

Name: A statistical program is recommended.Consider the following data for a
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Description: A statistical program is recommended.Consider the following data for a dependent variable y and two independent variables, x1 and x2.x1x2y301294471010825171125116178405945119175747170361211759131427616211 (a) Develop an estimated regression equation

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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x₁	x₂	y
30	12	94
47	10	108
25	17	112
51	16	178
40	5	94
51	19	175
74	7	170
36	12	117
59	13	142
76	16	211

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Suppose you are interested in the relationship between educational attainment (measured by years of completed schooling) and the how long people live (measured by age at death in years). For a sample of 100 recently-deceased people, you collect information on their educational attainment and their age at death. Treating educational attainment as the independent variable (X) and age at death as the dependent variable (Y), you compute the following regression equation. Y = 55 + 2.0X + e a) Interpret in words this equation. That is, what do each of the numerical values in the equation tell us? Be specific. b) How long would you predict that someone with a college education (that is, someone with 16 years of schooling) will live?
The admissions officer for a certain college developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high school GPA. ŷ = −1.39 + 0.0234x1 + 0.00482x2 where x1 = high-school grade point average x2 = SAT mathematics score y = final college grade point average. #1) The given regression equation follows where x1 is the high-school grade point average, x2 is the SAT mathematics score, and y is the final college grade point average. ŷ = −1.39 + 0.0234x1 + 0.00482x2 We are to predict the final college GPA for a student who has a high-school average of 84 and scored 535 on the SAT mathematics test. Thus, the corresponding values to substitute into the regression equation are x1 = and x2 = .
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.3 8.6 6.9 3.9 2.8 2.5 2.1 0.4 yy 13.8 11 9.7 7 6.7 6.5 6 4.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsDetermine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 1.1 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 6.1 thousand automatic weapons? Answer = Round to 3 decimal places.
1) create a line in DESMOS with the linear regression equation: y1 ~ mx1 + b 2) create a second line with quadratic regression: y1 ~ ax1^2 + bx + c After looking at the regression in DESMOS, is the data LINEAR or QUADRATIC?
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.3 7 3.4 2.4 2.6 2.6 0.9 yy 14 11.1 10.1 6.7 6.1 6.4 6.5 4.9 xx = thousands of automatic weaponsyy = murders per 100,000 residents Determine the regression equation in y = ax + b form and write it below. (Round to 2 decimal places):____________________ A) How many murders per 100,000 residents can be expected in a state with 10.8 thousand automatic weapons? Round to 3 decimal places. Answer = B) How many murders per 100,000 residents can be expected in a state with 4.4 thousand automatic weapons? Round to 3 decimal places. Answer =
The return rates of crane (Tagak) in Bulacan was studied using regression analysis and this relationship between return rate (x: % of birds that return to the colony in a givenyear) and immigration rate (y: % of new adults that join the colony per year) was established. The following regression equation was obtained: y = 31.9 – 0.34x. Based on this estimated regression equation, if the return rate were to decrease by 10% the rate of immigration to the colony would: A. increase by 3.4% B. decrease by 3.4% C. increase by 34% D. decrease by 0.34%
The grades of a sample of 9 students on a prelim exam (x) and on the midterm exam (y) are shown in the excel worksheet. Find the regression equation
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.7 8.3 7 3.8 2.6 2.6 2.7 0.9 yy 13.7 11.4 10 7.2 6.3 6 6.2 5.1 xx = thousands of automatic weaponsyy = murders per 100,000 residentsDetermine the regression equation in y = a + bx form and write it below. (Round to 2 decimal places) A) How many murders per 100,000 residents can be expected in a state with 2.4 thousand automatic weapons? Answer = Round to 4 decimal places. B) How many murders per 100,000 residents can be expected in a state with 2.3 thousand automatic weapons? Answer = Round to 4 decimal places.
In the linear regression equation,Y= 3(X) + 1, When X increases by 4 Points, why will increase by____ 4 point 13 points 12 points 7 points
The equation of the regression line that relates hours per week spent in the tutor lab, xx, to GPA, yy, is y=1.8+0.26xy=1.8+0.26x. a. What is the best prediction for the GPA of students who never go to the tutor lab? b. What is the best prediction for the GPA of students who spend 3 hours in the tutor lab? c. What is the best prediction for the GPA of students who spend 5 hours in the tutor lab?