Find a 95% confidence interval for the slope of the model below with nThe regression equation is Y = 85.8 8.89X.Predictor Coef SE Coef T PConstant 85.7994.353 19.71 0.000X-8.8862 1.0369 -8.57 0.000Round your answers to two decimal places.i!toi=24.

Explanation:To find a 95% confidence interval for the slope of the model, we need to calculate the…

Answered: Find a 95% confidence interval for the…

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 5SE: What does the y -intercept on the graph of a logistic equation correspond to for a population...

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Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
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?
Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?
A regression was run to determine if there is a relationship between hours of study per week (z) and the test scores (y)- The results of the regression were: y=ax+b a=5.701 b=31.89 r2=0.660969 r=0.813 Use this to predict the final exam score of a student who studies 3.5 hours per week, and please round your answer to a whole number. Question Help: Message instructor Submit Question rse here to search R
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=5.704 b=24.02 r2=0.436921 r=0.661 Use this to predict the final exam score of a student who studies 9 hours per week, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (x) and the test scores (y). The results of the regression were: y=ax+b a=6.813 b=21.42 r2=0.403225 r=0.635 Use this to predict the final exam score of a student who studies 6 hours per week, and please round your answer to a whole number.
The linear regression equation for a data set is ŷ = 1.2 – 3.2z. The actual value is -3.9, when z = 2. What is the residual value at x=2? residual:
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.
Assume a person got score of 32.5 on Test A and a score of 95.25 on Test B. Using the regression equation (B' = 2.3A + 9.5), what is the error of prediction for this person?
The estimated regression equation for a model involving two independent variables and 10 observations follows. ŷ = 26.0336 + 0.5179z1 + 0.7599x2 a. Interpret by and by in this estimated regression equation. %3D b1 y changes by 0.5179 when x1 increases by 1 unit and x2 stays the same y changes by 0.7599 when x2 increases by 1 unit and x1 stays the same b. Estimate y when a1 = 180 and æz = 310 (to 3 decimals).
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+ba=-0.759b=20.094r2=0.573049r=-0.757 Use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place)

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Find a 95% confidence interval for the slope of the model below with n The regression equation is Y = 85.8 8.89X. Predictor Coef SE Coef T P Constant 85.799 4.353 19.71 0.000 X -8.8862 1.0369 -8.57 0.000 Round your answers to two decimal places. i ! to i = 24.