There seems to be an outlier. Enter as a point: a. (x,y) : To determine if this is truly an outlier, we first need to find the standard error of the estimate, Se. Find the regression equation, round the slope and y-intercept to 2 decimals, and then use that equation to find the standard error. Round this answer to one decimal. b. Se = What y-value is the cutoff beyond which the point (5,33) would be considered an outlier? c. The cutoff is y

There seems to be an outlier. Enter as a point: a. (x,y) : To determine if this is truly an outlier, we first need to find the standard error of the estimate, Se. Find the regression equation, round the slope and y-intercept to 2 decimals, and then use that equation to find the standard error. Round this answer to one decimal. b. Se = What y-value is the cutoff beyond which the point (5,33) would be considered an outlier? c. The cutoff is y

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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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?
bThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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.
Suppose you decide to estimate a student consumption function. After you run an OLS regression on your data set with 36 observations, you obtain the following. The estimated regression, along with standard errors and t-statistics, CO = - 47.143 + 0.9714 YD (se) (2.0307) (0.157) (t) ( ) (6.187) Where, CO : the average annual consumption expenditures of the students on items other than tuition and room. YD : the average annual disposable income (including gifts) of the students a) Interpret the slope and the intercept. b) Compute the test statistics ( t value and critical t ) for the intercept of the regression. Note that significance level is 0.10.
Different hotels in a certain area are randomly selected, and their ratings and prices were obtained online. Using technology, with x representing the ratings and y representing price, we find that the regression equation has a slope of 125 and a y-intercept of −390.Complete parts (a) and (b) below. a. What is the equation of the regression line? b. What does the symbol y represent? A. The symbol y represents the predicted value of price. B. The symbol y represents the expected price when the hotel's rating is 0. C. The symbol y represents the average price of hotels in the area. D. The symbol y represents the amount that price increases with a 1-point increase in rating.
19. "A set of n = 50 pairs of X and Y scores has SSX = 39.73, SSY = 23.48, and SP = 42.91. What is the slope for the regression equation for predicting Y from X?"
How should the slope estimate of the following regression be interpreted (where wage is hourly wage and educexp is household average annual expenditure on education)? ln(wage)=11.4+8.13ln(educexp) A. When education expenditure increases by 1%, on average, hourly wages increase by 8.13 units. B. When education expenditure increases by 1 unit, on average, hourly wages increase by 8.13 units. C. When education expenditure increases by 1 unit, on average, hourly wages increase by 8.13%. D. When education expenditure increases by 1%, on average, hourly wages increase by 8.13% E. When education expenditure increases by 1, on average, hourly wages increase by 8.13.
A study was done of 6 patients admitted to a hospital. Their ages (x) and systolic blood pressure (y) was recorded. Age (x) Systolic blood pressure (y) 43 123 48 125 56 135 61 143 67 145 70 152 D. Compute the residual for x = 48, using the rounded slope and y intercept. Report answer to 3 decimal places. E. The data value of x = 56 has a residual of -0.575 If you were to make a scatter plot, which data point would be closer to the regression line? (56, 135) (48,125) (43,123) They are all the same distance from the regression line. F. Determine the value of se, reporting to 3 decimal places.
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n=15 college students. The SAT scores have a mean of M=580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation, r, then find r2.) C) Does the regression equation account for a significant portion of the variance in GPA? Use alpha = 0.05 to evaluate the F-ratio. A) b=0.00375; a=0.925; Y (hat) = 0.00375X+0.925 B) r= 0.5 r^2= 0.25
On a graph with common stock returns on the y-axis and market returns on the x-axis, the slope of the regression line represents: A) R-squared B) beta C) alpha D) standard err
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n = 15 college students. The SAT scores have a mean of M = 580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation r, then find r^2.) Does the regression equation account for a significant portion of the variance in GPA? Use α = .05 to evaluate the F-ratio.