The data in the following table shows the estimated Career Value Rating in relation to the Draft Pick Number for the NFL averaged over the last 25 years. Pick number Career value rating 5 10 15 20 25 30 40 50 100 200 64.6 52.7 45 39.2 37 32.1 33.1 27.8 27.4 18.2 10.5 Find the logarithmic model that fits this data. This type of model is called the logarithmic decay model. The logarithmic model that fits this data is y =. (Use integers or decimals for any numbers in the expression. Round to three decimal places as needed.)

The data in the following table shows the estimated Career Value Rating in relation to the Draft Pick Number for the NFL averaged over the last 25 years. Pick number Career value rating 5 10 15 20 25 30 40 50 100 200 64.6 52.7 45 39.2 37 32.1 33.1 27.8 27.4 18.2 10.5 Find the logarithmic model that fits this data. This type of model is called the logarithmic decay model. The logarithmic model that fits this data is y =. (Use integers or decimals for any numbers in the expression. Round to three decimal places as needed.)

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Part d
In doing regression analysis in MS Excel, what are the three sets of data you see from Regression result? Select all that apply. A. Probability Output B. Residual Output C. ANOVA D. Summary Output E. OVERALL Fit
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Determine whether the following table shows exponential data or linear data. x 0 5 10 15 y 62 135.9 298 653.4 a) The data are linear.b) The data are exponential.
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Your Question: A psychologist believed that as children get older, they engage in more “inactive activities” such as playing computer games, watching TV and surfing the internet. She collected data from 10 children. She recorded the age of each child and the amount of activity (in hours) the child engaged in per week. The data is below: Age Activity 7 4.3 9 3.2 10 1 13 1.5 12 1.2 15 0.8 9 3 12 4 15 1.5 14 1.9 Using excel, obtain a scatterplot of the data. Discuss the relationship between age and activity based on the scatterplot. Using excel, obtain the simple linear regression linear regression line predicting activity from age. Interpret the intercept and slope of the regression line. By hand, predict the amount of activity for age = 14. By hand, calculate the residual for age = 14. Using excel, test the null hypothesis that the slope coefficient is zero using the p-value approach. Write one sentence interpreting the meaning of this result. Make sure to…
Annabelle records the length, in inches, of a colored pencil over time. Review the table showing her data. Time (Weeks) Length (Inches) 0 7.5 2 7.5 4 7 5 6 7 2 8 1 10 0.5 12 0.25 13 0.2 Which description best fits the regression model for the data? logistic equation of the form y = , witha = 7.576, b = 0.001, and c = –1.107 logistic equation of the form y = , witha = 0.001, b = –1.107, and c = 7.576 trigonometric equation of the form y = a sin(bx + c) + d, with a = 4.15, b = 0.34, c = 497.43, and d = 3.80 trigonometric equation of the form y = a sin(bx + c) + d, with a = –4.15, b = –0.34, c = –497.43, and d = 3.80
Part D. Data from the Statistical Abstract of the United States provides a panel data collected at the state level in 1987 and 1990. These data are used to estimate MODEL 1: The variables used in the analysis are: infmort is number of deaths within the year per 1,000 live births Ipcinc is natural log of per capita income Ipopul is natural log of the population (the population is in thousands) Iphysic is natural log of physicians per 100,000 inhabitants d90 is year dummy for 1990. For questions 1 to 4 you can assume that MLR 1-4 are satisfied. A 1. Use the Stata output below to interpret ß3. Test at a 5% significance level whether the number of physicians per capita has any effect on infant mortality rate. reg infmort 1pcinc 1popul 1physic d90 Source Model Residual Total infmort infmort = Po + B₁lpcinc + B₂lpopul + ß3lphysic + 8₁ d90 + u SS 78.0499129 350.452136 428.502049 df . 19.5124782 4 97 3.61290862 Coef. Std. Err. MS 101 4.24259454 1pcinc -4.693354 1.638132 1popul - .0551426…
Consider a data set with the following descriptive statistics.(attached)Wage is the worker’s hourly wage; Black takes on a value of 1 if the worker is black and a value of 0 otherwise; work experience is actual years of work experience; schooling is measured in years; and percent female in occupation is the percent of all employees in the worker’s occupation who are female. The following table reports the regression results from a log-wage regression. Men Women Constant Black Age Years of work experience Years of schooling Percent female in occupation Number of observations R-squared 2.314 -0.198 0.054 0.042 0.085 -0.121 442 0.231 2.556 -0.154 0.037 0.059 0.083 0.002 278 0.254 Decompose the raw difference in average wages using the Oaxaca decomposition. Specifically, decompose the raw difference into the portion due to differences in personal characteristics (schooling, race, age, and experience), the portion due to occupation, and the portion left unexplained…
The table below is a record of the number of miles driven between stops for gas and the amount of money spent to fill up the gas tank in Audrey’s car over several months. Audrey’s Gas Fill Up LogMiles Driven, x 313 320 341 320 294 348 302Cost to Fill up ($), y 24.80 24.96 25.83 25.17 22.44 27.51 23.93 Step 2 of 2 : If Audrey needs to drive 319 miles home from college and leaves with a full tank, how much should she budget to fill up when she gets home? Assume the regression equation is appropriate for prediction. Round your answer to the nearest cent.
Would you include ros in a final model explaining CEO compensation in terms of firm performance?