Target due: 4/23/20Constructa scatterplot and identify the mathematical model that best fits the data. Assumethat the model is to be used only for the scope of the given data and consider only linear,quadratic, logarithmic, exponential, and power models. Use a calculator or computer toobtain the regression equation of the model that best fits the data. You may need to fitseveral models and compare the values of R2.Average sunset times are taken for six months across the summer. Giving the months April throughSeptember values 1 through 6, find the regression equation of the best model.month12.4 56.average sunset time in hours 19.51 20.87 21.45 20.64 19.32 18.20Dy = 21.20 – 0.343xOy= 20.62x 0.029y = -0.357x2 + 2.17x + 17.87Oy = 21.24 e0.983x11 of 15SubmitDescription

Let us define the variable X as the months and Y as the average sunset time in hours. Step-by-step…

Answered: Target due: 4/23/20 Constructa…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Biochemical oxygen demand (BOD) measures organic pollutants in water by measuring the amount of oxygen consumed by microorganisms that break down these compounds. BOD is hard to measure accurately. Total organic carbon (TOC) is easy to measure, so it is common to measure TOC and use regression to predict BOD. A typical regression equation for water entering a municipal treatment plant is BOD = -55.47 + 1.505 TOC Both BOD and TOC are measured in milligrams per liter of water. (a) What does the slope of this line say about the relationship between BOD and TOC? TOC rises (falls) by 1.505 mg/l for every 55.47 mg/l increase (decrease) in BOD BOD rises (falls) by 55.47 mg/l for every 1 mg/l increase (decrease) in TOC TOC rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in BOD BOD rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in TOC
An educator wants to see how the number of absences for a student in her class affects the student’s final grade by formulating the equation of the regression line. The data obtained from a sample are shown. Required: Slope of the regression line Only the final answer should be rounded-off to TWO decimal places.
NISH Boom Cardsl - Play boom.combg.com/play/1Dwb@fgH9jdMjFmxn/?Lenchcrld AYANWBBrodXKJA its X + 000000000000000000000 13 boomcardsk Use the following regression equation to predict the height of an 8-year-old American girl. Round all answers to the nearest hundredth (2 places after the decimal) and type it in the space below. y = 2.59x + 29.31 An average 8-year-old American girl is approximately 5 centimeters tall. W y tip Type here 90 C Submit X Give up Skip Q Overview ★ Save Card O P Dec 3 1
Can brand, battery life, and camera resolution affect a smartphone's price? Use α = .05 to perform a regression analysis for the Smartphones01BC dataset and answer the following questions. Solve this problem using MegaStat, and write your complete answers in the Response Box so I know that you can interpret the output. Attach your MegaStat file so I can see that you used the correct analysis method to solve this problem. Download: Smartphones01BC a. Perform the regression and write the complete regression equation. b. Based on your regression equation, which brand increases the price of a smartphone the most? Use the statistics from your output to explain your answer. c. Which predictors are significant, and which are not? Use the statistics from your output to explain your answer. d. Use your regression equation to predict the price of an LG smartphone with a 40-hour battery and 12-megapixel camera.
Two variables are defined, a regression equation is given, and one data point is given. Weight Training = = Weight 92 +11.9(Training) = maximum weight capable of bench pressing (pounds) number of hours spent lifting weights a week The data point is an individual who trains 5 hours a week and can bench 150 pounds. Residual (a) Find the predicted value for the data point and compute the residual. Enter the exact answers. Predicted value = M. lbs lbs
Answer d,e and f
please solve all parts as soon as possible
Illustrate the importance of using regression models.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? Find the equation of the regression line. (Round the constant three decimal places as needed. Round the coefficient to six decimal places as needed.) The best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports is _______ fatalities per 100,000 population. (Round to one decimal place as needed.) Is the prediction worthwhile? A. Since the sample size is small, the prediction is not appropriate. B. Since common sense suggests there should not be much of a relationship between the two variables, the prediction does not make much sense. C. Since all of the requirements…
The data show The chest size and weight of several bears find regression equation, letting chest size be the independent variable then find the best predicted weight of a bear with a chest size of 51 inches is the result close to the actual weight of 422 pounds use a significance level of 0.05 Chest size : 45, 50, 43, 43, 52, 52. Weight : 352, 374, 275, 314, 440, 367.
Need help finishing the regression equation with the following: Y=Residents' Preference B=Size of sector budget, sector budget, and individual trust as Independent Variables. I'm using Jamovi software, but the need to create the equation with information above. Thanks,

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