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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Can you contruct a 95% confidence interval for the Y intercept for the regression equation. Then explain what do you conclude from this regression?
Hi I know that you can’t answer all questions. Can you just answer question 15 please.
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
How can I find this in the chart and work it out ?
stion 4 of 14 > The scatterplot given compares data on the fuel consumption y of a car at various speeds x. Fuel consumption is measured in liters of gasoline per 100 kilometers driven, and speed is measured in kilometers per hour. A statistical software package gives the least-squares regression line ŷ = 11.058 +0.01466x. 10.0 - Use the residual plot to determine if this linear model is 75 appropriate. O No. There is an obvious positive- negative - positive 5.0 - pattern in the residual plot so a linear model is not appropriate for these data. O Yes. There is an obvious positive – negative – positive pattern in the residual plot so-a linear model is appropriate for these data: O No. The residuals do not have equal variability in the residual plot so a linear model is not appropriate for 2.5 - -2.5 -5.0 - 20 40 60 80 100 120 140 160 these data. Speed (km/h) O No. The residuals are not equally positive or negative in the residual plot so a linear model is not appropriate for these data.…
Hi I know that you can’t answer all questions. Can you just answer question 16 please.
Bivariate data obtained for the paired variables x and y are shown below, in the table labeled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this line is y = 14.87+0.88x. In the "Calculations" table are calculations involving the observed y-values, the mean y of these values, and the values y predicted from the regression equation. Sample data Calculations 160+ x y (x-1)² (-5)² (v-^^)² 150+ 107.2 110.7 396.0100 457.7032 2.2320 122.0 130.3 140- 0.0900 70.0569 65.1249 131.5 122.1 130- 72.2500 0.0001 72.0801 142.5 129.9 120. 0.4900 93.5089 107.5369 152.5 160.0 110- 864.3600 341.1409 119.4649 Send data to Excel LL 130 130 140 150 160 Column sum: 1333.2000 Column sum: 962.4100 Column sum: 366.4388 Figure 1 Answer the following. (a) The least-squares regression line given above is said to be a line that "best fits" the sample data. The term "best fits" is used because the line has an…
[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
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
Chest_size_(inches) Weight_ (pounds)58 42548 26651 34758 45344 28260 408
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