Part 3 101 1122. Having computed A from #1 above:I. Write down the equation of the best fit line (i.e. the estimation function), noting that the first entry of A is theintercept and the second, the slope.II. Compute Ŷ = FA, i.e. where the data point should have been to lie exactly on the line.3. Next, compute the least squared error E = ||Y – Ý|| ²/NOTE: All computations must be done by hand. Show detailed steps taken.1. Given that F=2Y:68.-compute A = (FT F)−¹ FTY.

Here, in the question it is given matrix F and we have compute A= ( FTF)-1FTY. Now after that we…

Answered: 1. Given that F = 6 1,Y= 0 , compute A…

Mathematics For Machine Technology

8th Edition

ISBN:9781337798310

Author:Peterson, John.

Publisher:Peterson, John.

Chapter38: Achievement Review—section Three

Section: Chapter Questions

Problem 6AR

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bThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.
Use the table of values you made in part 4 of the example to find the limiting value of the average rate of change in velocity.
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
You build a linear model to predict Calc2 grades from Calc1 grades. Residuals: Min: -17.674 1Q: -6.759 Median: 0.899 3Q: 6.725 Coefficients: Estimate Std. Error t value (Intercept) 11.866 12.6782 gradeCalc1 0.9581 0.4149 2.309 Residual standard error: 11.299 on 98 degrees of freedom Multiple R-squared: 8.98, Adjusted R-squared: 8.531 F-statistic: 50 on 1 and 98 DF, p-value: 2.290764244961E-10 Max: 15.674 Pr(>It|) 0.1746 0.0105
Find the slope of the normal line to the function g(x)=Vr² +7 at x=3. Select one: 4 а. 3 4 b. 3 3 C. 4 3 d. 4
5
a) Calculate the average time per lap (in s) for student 2. b) Calculate the uncertainty (ie. the standard error, in s) on the average time per lap for student 1. c) From the experimental data, it is possible to find a student's average speed as he runs around the track. Calculate the average speed (in m/s) for student 2 as he runs the 6 laps. d) Make a plot of the cumulative times vs. cumulative distances for student 1. To clarify, your first data point would be (400 m, 55 s) and your second data point would be (800 m, 112 s), etc... From the slope of a linear regression of your graph, calculate the average speed (in m/s) for student 1 as he runs the 6 laps
This question had 6 parts and I was ask to resend the last 3. the question is The line of best fit for a data set is y= 1.1x+3.4. Find the residual for each of the coordinate pairs (x,y).
Accountants at the Tucson firm, Larry Youdelman,CPAs, believed that several traveling executives were submittingunusually high travel vouchers when they returned from businesstrips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regres-sion equation relating expected travel cost to number of days on the road ( x1 ) and distance traveled ( x2 ) in miles:yn = +90.00 + +48.50x1 + +.40x2The coefficient of correlation computed was .68.a) If Donna Battista returns from a 300-mile trip that took herout of town for 5 days, what is the expected amount she shouldclaim as expenses?b) Battista submitted a reimbursement request for $685. Whatshould the accountant do?c) Should any other variables be included? Which ones? Why?
Residuals are the: 1.horizontal deviations from the line of best fit to each data point 2.perpendicular distances from the line of best fit to each data point 3.vertical deviations from the line of best fit to each data point 4.areas of the squares between the line of best fit and each data point
The variance of the slope estimator B, Select one: а. increases as the error variance decreases and increases when there is more sampling variation in the independent variable. O b. increases as the error variance increases and decreases when there is more sampling variation in the independent variable. O c. decreases as the error variance decreases and increases when there is more sampling variation in the independent variable. O d. decreases as the error variance increases and decreases when there is more sampling variation in the independent variable
Please do & explain with steps: Subparts e f & g please & thank u

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