Question 9 ignore this just keeping track Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regressionline.X 11-7y 15.51 11.51A.Ayy=+x (Round to two decimal places as needed.)Create a scatterplot of the data. Choose the correct graph below.25-20-15-10455.32 7.69Soooo 0.0.06 14 109.76 15.32 14.975-0-0 5 10 15 20 25B.Ау25-20-15-310-510-01215.7609.005 10 15 20 25914.12QQG13 815.69 12.97OC.Ау25-20151035-30-0 5 10 15 20 2500.00 DEQOUOD.AY25-20-000000000015-10-5:0-0 5 10 15 20 25QOU27

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Answered: Use the given data to find the equation…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section4.3: Fitting Linear Models To Data

Problem 34SE: For the following exercises, consider this scenario: The profit of a company decreased steadily...

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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?
For the following exercises, consider this scenario: The profit of a company decreased steadily overa ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Use linear regression to determine a function Pwhere the profit in thousands of dollars depends onthe number of units sold in hundreds.
A set of n = 5 pairs of X and Y scores has SSX = 6, SSY = 18, and SP = 42. What is the slope for the regression equation for predicting Y from X? Select one: a. 7 b. -8 c. 4 d. -5
According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume thatA has any value. If we decrease the value of A by 3, how would Y be affected?a) 58.8945 decreaseb) 58.8945 increasec) 29.8827 increased) 49.5142 decreasee) 29.8827 decrease
Draw the regression line for the following equation: Y = -3 + (1) X Show your calculation for a low and high value on the predictor value.
Assume there is a positive linear correlation between the variable R (Return rate in percent of a financial investment) and the variable t (age in years of the investment) given by the regression equation R= 2.3t + 4.8 A. Without further information, can we assume there is a cause-and-effect relationship between the return rate and the age of the investment? B. If the investment continues to grow at a constant rate, what is the expeted return rate when the investment is 7 years old? C. If the investment continues to grow at a constant rate, how old is the investment when the return rate is 30%?
Consider the set of ordered pairs shown below. Assuming that the regression equation is y= 2.814 + 0.406x and the SSE = 5.313, construct a 90% prediction interval for x= 3. x 6 0 4 4 4 2 y 5 3 6 5 3 3 Calculate the upper and lower limits of the prediction interval. UPL=LPL= Someone please help me solve this! Thank you!
The overall purpose of regression analysis is: a) to lessen our error in making predictions b) to make perfect predictions, since all data points must fall on the regression line c) to exploit the correlation between Y and X and use it to help make better predictions of Y d) two of the above e) three of the above f) none of the above
1. For the data below, the coefficient of determination is : provide answer to 4 decimal places with the correct sign and a leading zero examples, 0.2548 -0.8596 2. The slope of the linear regression equation is : provide answer to 4 decimal places with the correct sign and a leading zero if applicable examples, 0.2548 -0.8596 20.2356 -6.4258 3. Predict the Grocery Cost in Dollars per Person when the number of people in the family is 5: provide answer to 2 decimal places , no dollar sign is needed examples, 8.75 42.36
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. Length, x Girth, y 136 105 168 131 151 117 144 106 160 126 159 119 123 102 138 103 156 120 147 111 148 106 147 109 The equation of the regression line is ŷ = ______ x + ______ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (a) x = 140 cm, (b) x = 172 cm, (c) x = 164 cm, (d) x = 158 cm Use the regression equation to predict…
A study was done that examined the effectiveness of a 7-Minute Screen test for Alzheimer’s disease. The study evaluated the relationship between scores from the 7-Minute Screen and scores for the same patients from a set of cognitive exams that are typically used to test for Alzheimer’s disease. For a sample of n=9 patients, the scores for the 7-Minute Screen averaged M=7 with SS = 92. The cognitive test scores averaged M=17 with SS = 236. For these data, SP = 127. Find the regression equation for predicting the cognitive scores from the 7-Minute Screen score. b = a = Regression equation = What percentage of variance in the cognitive scores is accounted for by the regression equation? r = r2 = Does the regression equation account for a significant portion of te variance in the cognitive scores? Use α = .05 to evaluate the F ratio. MSregression = MSresidual = Fcalculated = Fcritical = Decision =

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