Subject : Statestic Given are five observations for two variables, and y.SSESST0.16SSR70YiThe estimated regression equation for these data is ŷ = 0.9 +2.5x.a. Compute SSE, SST, and SSR using the following equations (to 1 decimal).SSE = Σ (y - ;)- v)SST = Σ (ySSR=(9.-7)²**xi*13268b. Compute the coefficient of determination ² (to 3 decimals).Does this least squares line provide a good fit?Yes, the least squares line provides a very good fitc. Compute the sample correlation coefficient (to 4 decimals).73A8410514

xi yi 1 3 2 7 3 8 4 10 5 14 the regression equation is y^=0.9+2.5*x

Answered: Given are five observations for two…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.8: Fitting Exponential Models To Data

Problem 1TI: Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use...

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Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.
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What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
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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?
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y).
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Which of the following represents a regression line. a. y = 12.82x (0.24x - 2.56) b. y = -0.57x - 7.73xy c. y = - 0. 37x + (0. 26x - 6.16) d. y= x ( 0.92x + 12.33 )
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The prelim grades (x) and midterm grades (y) of a sample of 10 MMW students is modeled by the regression line y = 12.0623 + 0.7771x. Estimate the prelim grade if the midterm grade is 83.

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