I need answer within 20 minutes please please with my best wishes Q.8). In a regression calculation, a researcher finds that the explanatory variable x hasmean 100 and SD 10, and the response variable y has mean 250 and SD 40. Theregression equation is found to be y= 450 – 2x. What is the correlation between x andу?(a) cannot tell from the information available(b) -0.8(с) -0.5(d) 0.4(е) 0.1

Answered: Image /qna-images/answer/b3a60a03-ae5f-4128-b237-34c1ebbe6fd6.jpg

Answered: Q.8). In a regression calculation, a…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.5: Correlation And Causation

Problem 24PFA

See similar textbooks

Similar questions

What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
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?
10) 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=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
4b) The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression equation, using the first variable x (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure (y) reading of 140. What is the correlation coefficient, r? Using a significance level of a = 0.05, is there a significant linear relationship between systolic and diastolic blood pressure? Blood Pressure: Systolic Diastolic 112 125 115 136 143 116 123 124 elimii 70 89 65 90 97 64 SUTT nisinoo aqdM 21.SS bns aqdM 78 ahoqnis erit te zbesqz steb ils to 69 bns ago 20.EI to adimil srit terit sonabilnos 2 nistnoo aqdM 21.SS bnc agdM sgsavs arit ferli mislo a hoqnis orti roqque lovedni sonsbilnos 3028 wolsd insmsisiz tomo artezorio SeqdM 2.55 al 2.SS to sulavadi znistmoodi ezusaed mish ads toqque ton zaob 2.55 to sulsy sdt anistroo ti sausosd mislo ert hoqquz 200b to sulav orit nisinoo ton zoob 11 saussed misbb adi…
The correlation coefficient computed for the relationship between a dependent variable Y and an independent variable X is -0.35. This result means thatA. 35% of the variation of the dependent variable Y is due to the linear relationship between Y and X.B. 12.25% of the variation of the dependent variable Y is due to the linear relationship between Y and X.C. There is a weak, negative relationship between Y and X.D. There is a very weak, negative relationship between Y and X.
Data comprises of the number of hours studied (X) and the exam grade (Y) obtained for 6 first year students registered at UWC. The equation of best fit is given by: y = 67.071 + 4.535x. The correlation coefficient is found to be 0.557, which implies that the coefficient of determination is . ., and that O A. 0.7463, about 74.6% of the variation in Y is explained by the estimated line of best fit. O B. 55.7%, the time (in hours) spent studying has a positively correlation with the grade obtained in the exam. O C. 0.310, about 31% of the variation in Y is explained by the estimated line of best fit. O D. 0.557, about 55,7% of the variation in Y is explained by the estimated line of best fit.
The table below gives the age and bone density for 5 women. Use the equation of the regression line, y= b0 + b1x, for predicting a women's bone density based on her age. The correlation coefficient may or may not be statically significant for the data given. Remember it wouldn't be appropiate to use regression line to make a prediction if the correlation coefficient isn;t statically significant. (y has a "hat" on the top) age 39 51 54 56 67 bone density 355 349 347 315 313 Find the estimated slope. Rund your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine the value of the dependent variable y at x+ 0 (y has a "hat" onthe top) Find the estimated value of y when x = 51. Round your answer to three decimal places. Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the valueof the…
A researcher collected data on people's heights and their shoe sizes from 500 people (N=500). Then, she convert the two variables (X-: heig ht, Y: shoe size) to standard scores before computing regression constants and the correlation coefficient between the two variables. The correlation coefficient (from the standardized scores) was found to be r = .37. Which of the following statements is CORRECT? a. Although the correlation coefficient is positive (r=.37), the regression slope can be negative O b. If the correlation coefficient was computed from raw scores, it will not be r=.37 O c. The regression slope (from the standardized scores) is the same as the correlation coefficient (r=.37) Od. The Y-intercept (from the standardized scores) is the same as the correlation coefficient (r=.37)
In a study of possible correlation between the height in cm (X) and the weight in kg (Y) of chimpanzees, a sample of 40 animals produces a correlation coefficient of r = 0.813 and a regression line with equation Y = 0.34X + 19.5. What is the expected weight of an 80cm tall chimpanzee? O A) 177.9 kg O B) 34.8 kg OC)24.0 kg OD) 46.7 kg
The regression equation for for the association between BMI and total cholesterol level is: y = 28.07 + 6.49x A.) Suppose a participant has a BMI of 26. What would we estimate the total cholesterol to be? B.) Suppose two individuals have a mean BMI that differs by 3 units. What is the estimated difference in total cholesterol. C.) What ranges of BMI should the equation be used to predict total cholesterol?
In a regression calculation, a researcher finds that the explanatory variable x has a mean 100 and SD 10, and the response variable y has a mean 250 and SD 40. The regression equation is found to be y-cap =450-2x. What is the correlation between x and y?
Suppose IQ scores were obtained from randomly selected siblings. For 20 such pairs of people, the linear correlation coefficient is 0.867 and the equation of the regression line is y = 3.57 + 0.97x, where x represents the IQ score of the younger child. Also, the 20 x values have a mean of 96.75 and the 20 y values have a mean of 97.1. What is the best predicted IQ of the older child, given that the younger child has an IQ of 95? Use a significance level of 0.05. Click the icon to view the critical values of the Pearson correlation coefficient r. The best predicted IQ of the older child is (Round to two decimal places as needed.)

SEE MORE QUESTIONS

Recommended textbooks for you

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

College Algebra

Algebra

ISBN:

9781938168383

Author:

Jay Abramson

Publisher:

OpenStax

Big Ideas Math A Bridge To Success Algebra 1: Stu…

Algebra

ISBN:

9781680331141

Author:

HOUGHTON MIFFLIN HARCOURT

Publisher:

Houghton Mifflin Harcourt

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

College Algebra

Algebra

ISBN:

9781938168383

Author:

Jay Abramson

Publisher:

OpenStax

Big Ideas Math A Bridge To Success Algebra 1: Stu…

Algebra

ISBN:

9781680331141

Author:

HOUGHTON MIFFLIN HARCOURT

Publisher:

Houghton Mifflin Harcourt

Functions and Change: A Modeling Approach to Coll…

Algebra

ISBN:

9781337111348

Author:

Bruce Crauder, Benny Evans, Alan Noell

Publisher:

Cengage Learning

College Algebra

Algebra

ISBN:

9781305115545

Author:

James Stewart, Lothar Redlin, Saleem Watson

Publisher:

Cengage Learning

SEE MORE TEXTBOOKS