What is the equation of the least-squares regressionAn analysis of the decay of 10 grams of an unstableelement over time was completed and is displayed inline?the computer output.O Element = 2.305 0.101 In(Time)Regression Analysis: In (Element) versus TimePredictorCoefSE CoefPO In(Element) = 2,305 - 0.101(Time)Constant2.305 0.021109.760.000Time-0.101 0.0007-132.990.000s=0.0079R-Sq=0.99R-Sg (adj)=0.999O In(Element) = -0.101 + 2.305(Time)O In(Time) = -0.101 + 2.305 (Element)Mark this and returnSave and ExitNextSubmit67°FDELLF3E4E5F6F8F9F10F11F12PriScrInsert%23%24%&4.710EDGJ K

Answered: An analysis of the decay of 10 grams of…

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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Give an interpretation of the term “R-sq” and comment on its value.
894c3d916%#10001 MAT 213 OL1 Elementary Statistics Shayjunna Jones &| 0| 02/03/21 4:56 PM Homework: Homework 3 Save Score: 0 of 3 pts 17 of 20 (3 complete) ▼ HW Score: 10%, 6 of 60 pts 4.2.50 Question Help v Use the given data to do the following. a. Find the regression equation for the data points. b. Graph the regression equation and the data points. 4 3 y 4 -1 9 3 a. Find the regression equation for the data points. y = (Round to two decimal places as needed.) Enter your answer in the answer box and then click Check Answer. Check Answer 1 part remaining Clear Al 4:56 PM 2/3/2021 Cip
Compute the least-squares regression line for predicting the number of stays from the cost. Round your answers to four decimal places.
[Simple Regression on House Price] Consider the following model you wish to estimate by using the OLS, Price = α + β sqrft + ε, where price is the house price in thousands of dollars and sqrft is size of house in square feet. The OLS result from Excel is as follows (see attached). At the 0.05 level of significance, is there enough evidence that the true population regression coefficient β is different from zero (i.e., H1: β≠0)? (a) Yes (b) No (c) We don’t have enough information to decide
the regression model using 240 monthly observation stock return = bo+b,*size+b,*CM+b;+profitability+b,investment +e coefficien standard error bo -0.01 0.03 b1 0.22 0.25 b2 0.02 0.13 b3 0.03 0.08 b4 0.04 0.06 df sum residual squared regression 4 0.095 Which one of the four variable can explain the time variation in stock return given 95% confidence level? Is the four-factor model is better than the random walk model in explain the return given 95% confidence level?
Consider the accompanying data set of dependent and independent variables a. Perform a general stopwise regression using a 0.05 for the p-value to enter and to remove independent variables from the regression model b. Perform a residual analysis for the model developed in part a to verify that the regression conditions are met Click the icon to view the data a. Use technology to perform the general stepwise regression What is the resulting regression equation? Note that the coefficient is 0 for any variable that was removed or not significant -0.69 (050), (050)+(018) - X (Round to two decimal places as needed) • Data Table: y 63 43 51 49 40 42 23 37 30 27 20 31 FR 74 63 78 3534 52 44 47 35 17 15 20 17 Print X₂ 21 259. 15 9 38 18 17 5 40 27 30 33 x₂ 22 aadosa 2NNG 29 20 17 13 17 8 15 10 10 Done 1
What does the slope and the intercept mean in this setting?
12 A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy).The results of the regression were: y=ax+b a=5.531 b=23.45 r2=0.378225 r=0.615 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole numbe
Which of the following is FALSE? * The residuals in a regression model are assumed to have a zero mean. Data point below the regression line, the residual is negative. The residuals in a regression model are assumed to have increasing mean. The regression model assumes the residuals are normally distributed.
Chest_size_(inches) Weight_ (pounds)58 42548 26651 34758 45344 28260 408
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