Identify the best mathematical model and it's r^2 value. Is it a good fit? **Problem:** A fitness trainer decided to track the combined weight loss of several new customers. She recorded the combined weight loss each month and kept track for 6 months. Identify the best mathematical model with its corresponding \( R^2 \) value and tell whether it is a good model.**Data Table:**| Month | 1 | 2 | 3 | 4 | 5 | 6 ||-------------|-----|-----|-----|-----|-----|-----|| Weight Loss | 175 | 120 | 95 | 63 | 44 | 33 |**Model Evaluation:**1. **Exponential Model, \( R^2 = 0.996 \):** - No, 0.966 is too high an \( R^2 \) value.2. **Quadratic Model, \( R^2 = 0.994 \):** - No, 0.994 is too high an \( R^2 \) value.3. **Exponential Model, \( R^2 = 0.996 \):** - Yes, 0.996 is very close to 1.4. **Quadratic Model, \( R^2 = 0.994 \):** - Yes, 0.994 is very close to 1.

Name: Identify the best mathematical model and it's r^2 value. Is it a good
Uploaded: 2024-03-20T07:07:26.000Z
Channel: Bartleby
Description: Identify the best mathematical model and it's r^2 value. Is it a good fit? **Problem:** A fitness trainer decided to track the combined weight loss of several new customers. She recorded the combined weight loss each month and kept track for 6 months

Exponential: Steps to construct scatter plot in Excel: Enter the data for Month and Weight Loss…

Math

Statistics

. A fitness trainer decided to track the combined weight loss of several new customers. She recorded the combined weight loss each month and kept track for 6 months. Identify the best mathematical model with its corresponding R value and tell whether it is a good model. Month 2 9.

. A fitness trainer decided to track the combined weight loss of several new customers. She recorded the combined weight loss each month and kept track for 6 months. Identify the best mathematical model with its corresponding R value and tell whether it is a good model. Month 2 9.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

P (Z>)=0.8869
Pls help with below homework-) Show transformation of switching equation into a regression equation.
Illustrate the importance of using regression models.
A researcher is using the regression model Y=61+4.5X to predict a persons score on a happiness questionnaire based on their number of friends Predict the happiness score for someone with 8 friends
Explain what a residual is and how this relates to the best-fit regression model.
How to know if obtaining a regression equation for the data appear reasonable?
How should I draw this linear regression graph for this model? Thanks.
What are some important applications of regression analysis in the real world?
please explain with an example.
Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value t,/2, (b) find the critical value z,12, or (c) state that neither the normal distribution nor the t distribution applies. 40- The confidence level is 95%, o is not known, and the histogram of 58 player salaries (in thousands of dollars) of football players on a team is as shown. 30- 20- 10- 4000 8000 1200 1600 20000 Salary (thousands of dollars) Select the correct choice below and, if necessary, fill in the answer box to complete your choice. O A. ta/2= (Round to two decimal places as needed.) OB. Za/2 = (Round to two decimal places as needed.) O C. Neither the normal distribution nor the t distribution applies. houanbo
Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing. Call: lm(formula = score ~ list, data = hearing) Residuals: Min 1Q Median 3Q Max -14.7500 -5.5833 -0.2083 6.3333 16.4167 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 32.750 1.612 20.315 < 2e-16 *** listList2 -3.083 2.280 -1.352 0.17955 listList3 -7.500 2.280 -3.290 0.00142 ** listList4 -7.167 2.280 -3.144 0.00225 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 7.898 on 92 degrees of freedom Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101 F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
Explain the Regression Functions That Are Nonlinear in the Parameters?