Data on the average Scholastic Aptitude Test verbal and mathematics scores for high school seniors in each of the fifty states show a strong straight-line association. The regression line for predicting a state’s average math score (y) from the average verbal score (x) is y = 1.03x – 5 The average SAT verbal score in New York was 433. Use the regression line to predict New York’s average math score.

Data on the average Scholastic Aptitude Test verbal and mathematics scores for high school seniors in each of the fifty states show a strong straight-line association. The regression line for predicting a state’s average math score (y) from the average verbal score (x) is y = 1.03x – 5 The average SAT verbal score in New York was 433. Use the regression line to predict New York’s average math score.

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 2AGP

See similar textbooks

Similar questions

Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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?
If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
In a fisheries researcher's experiment, the correlation between the number of eggs in the nest and the number of viable (surviving) eggs for a sample of nests is r = 0.67. The equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y = 0.72x + 17.07. For a nest with 140 eggs, what is the predicted number of viable eggs?
Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
A medical researcher wants to determine how a new medication affects blood pressure. An amount of medication of 145 mg is found to result in a blood pressure of 128.42 mm Hg. What is the predicted blood pressure? Where is the observed value in relation to the regression line? The equation of the regression line is �^=140+(−0.0667)�. Where is the observed value in relation to the regression line? An amount of medication of 178 mg is found to result in a blood pressure of 128.13 mm Hg. What is the predicted blood pressure? Where is the observed value in relation to the regression line? An amount of medication of 200 mg is found to result in a blood pressure of 129.15 mm Hg. What is the predicted blood pressure? The options for the drop down boxes are below, above or on the regression line.
A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table at the bottom of this page. a) Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student ( this assignment is arbitrary) complete the regression equation for the model below, where y= Score, x1= GPA, x2= Hours, x3= Absenses, and x4= Gen. y= (__) + (__)x1 + (__)x2 + (__)x3 + (__)x4 b) Test the significance of the overall regression model using a= 0.10. c) interpret the meaning of the regression coefficient for the dummy variable. d) using the p-values, identify which independent variables are significant with a= 0.10. e) construct a regression…
A car dealer wants to estimate the price of a used car based on the age of the car and the mileage. Based on a sample of 20 cars, she determines the sample regression equation that predicts price taxes on the basis of the age (in years) of the number of miles is Price=21,619-1022Age-0.03 Miles (a) If the age of the car was fixed and the mileage was increased by 10,000, how much would the price increase or decrease and by how much? (b) Predict the selling price of a five-year-old car with 65,000 miles. (Round your answers to the nearest whole number.)