fitting a least square line to n = 14 data points, the quantities below were computed. SSxx = 25 x-bar = 4 SSyy = 22 y-bar = 3 SSxy = 23 Find the following: (Show work) a- Find the least square line (Y-hat = Y-intercept + Slope * x) b- Calculate SSE c- Calculate s^2

fitting a least square line to n = 14 data points, the quantities below were computed. SSxx = 25 x-bar = 4 SSyy = 22 y-bar = 3 SSxy = 23 Find the following: (Show work) a- Find the least square line (Y-hat = Y-intercept + Slope * x) b- Calculate SSE c- Calculate s^2

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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Given the data as shown in the table below X Y 56 0.86 44 0.93 68 0.85 76 0.87 94 0.73 a) Using �^=-0.0034�^+1.0798 as the equation of the "Best-Fit" line. Calculate the residuals, �-�^, of this data:�1=56, �1-�^1 = −0.0292Incorrect . Round your answer to 4 decimal places.�2=44, �2-�^2 = 0.0000Incorrect . Round your answer to 4 decimal places.�3=68, �3-�^3 = 0.0016Incorrect . Round your answer to 4 decimal places.�4=76, �4-�^4 = 0.0488Incorrect . Round your answer to 4 decimal places.�5=94, �5-�^5 = −0.0300Incorrect . Round your answer to 4 decimal places.b) Using the formula��=�12+�22+⋯+��2�-2calculate the standard deviation, ��, of all residuals.��=0.0371Correct . Round your answer to 4 decimal places. Question HelpQuestion 4: Message Message instructor Submit QuestionQuestion 4
A least squares line for a sample with 11 observations has an SSE = 192; calculate and s. Please show your work So i can understand how you arrived at the answer
Describe in detail about regression lines?
3. Solve for B. The accompanying data are from a football league for one season. Use the regression tool to develop a model for predicting points/game as a function of yards/game. Explain the statistical significance of the model and the r^2 value. Solve for B Develop a mod for predicting points/game as a function of yards/game. Points/game= -20.892 + (.131) x yards/game. To Explain the statistical significance of the model first state the appropriate null and alternative hypotheses. H0 : H1: SEE PICTURE
Given the “data” determined by y = x^3 + (x-1)^2 with x = 0.1, 1.2, 2.3, and 2.9, calculate SSTO, SSR, and R^2. Then recalculate these using x = 0.3, 1, 2.45, and 2.8. Does where you collect your data (i.e., which values of x) appear to impact your interpretation of how good the linear model fits?.
Describe in your own words what it means to perform a linear least squares analysis. Provide an example to substantiate your claims
Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin, - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team===== "Brooklyn Nets" . Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 None of the above 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 MS t Number of obs F(1, 80) Prob > F R-squared O The Nets lost more games than they won in 2014 P>|t| 2.77 0.007 -2.42 0.018 Adj R-squared = Root…
A frequent flyer was interested in the relationship between dollars spent on flying and the distance flown. She sampled 20 frequent flyers of a certain airline. She collected the number of miles flown in the previous year and the total amount of money the flyer spent. A regression line of distance flown on money spent was fit to the data: \hat y = 24000 + 10xy^=24000+10x. A person who spent $1000 is predicted to have flown:
The table below represents the values of discharge and stage. Extend the rating curve for these data, using the following equations [q= k(g-a), k= 10^, a=0]. Try to estimate the values of k and b by least square method. Determine the value of discharge at stage 7m. Stage (m) 5. 4 2 Discharge (m'/s) 50 20 10
Using the guide of the textbook and your RQ, determine the equation of the least-square line for the following data: 1 6 3. Select the correct answer in the slope-intercept form. O y=-x+10.5 O y=-2x+11 O y=x O y=x+10 O x+y=11
Does the Regression line give information about all the data points in the data set? Does the Regression line usually have all the points in the data set on it?
Students who are going to college have a cost per credit. The chart below is a cost of tuition cost increase over the years. A table of the yearly cost is listed below. A) Use technology (graphing calculator or excel) to determine the least squares regression line for the best fit line for the data given above. List the equation and R^2 Regression factor. B) Use your equation from technology to estimate how much college credits will cost in 2021