pl use R code to do that and show me the program Use a linear regression...

pl use R code to do that and show me the program

Use a linear regression of Y~log(X) using the labtestdata.csv data to predict Y (2dp) when x = 250 on the unlogged scale?

Calculate the F-value (1 dp) from an ANOVA on the regression of Y~log(X) using the data contained in labtestdata.csv

abtestdata.csv

y	x
1.018746	1
1.508895	2
0.727282	3
1.787127	4
2.903983	5
3.181554	6
1.737834	7
2.715766	8
1.570552	9
3.046107	10
4.499675	11
4.240688	12
3.326716	13
4.626502	14
4.44944	15
3.861936	16

Expert Solution

As requested, the R code with commented explanation is provided to solve the given problem,

_____________________________________________________________________________________________

> d = read.csv("labtestdata.csv",header = T)  ## importing the data
> d

> fit = lm(y~I(log(x)),data=d)    ## fitting the required regression model
> summary(fit)                    ## details of the fitted model

> predict(fit,data.frame(x=c(250)))        ## value of Y for X = 250

> summary(aov(fit))                        ## Details on Anova of the fitted model

##### Please note : the above F Value is the required solution.####

orchestra answered 2 years ago

Can someone show me the R code to accomplish this? In R, Construct scatter plots of...

Can someone show me the R code to accomplish this? In R, Construct scatter plots of y versus x, y versus ln(x), ln(y) versus ln(x) and 1/y versus 1/x. Include your R code in a separate file. The article “Reduction in Soluble Protein and Chlorophyll Contents in a Few Plants as Indicators of Automobile Exhaust Pollution” (Intl. J. of Environ. Studies, 1983: 239-244) reported the accompanying data on x distance from a highway (meters) and y lead content of soil...

pl use r studio to do that What is the most appropriate analysis to perform on...

pl use r studio to do that What is the most appropriate analysis to perform on the following data? x<-c(8.1, 9.4, 9.9, 9.6, 10.7, 10.2, 10.4, 13.6, 15.5, 17.8) Y<-c(7.3, 8.6, 9.9, 9.6, 9.3, 9.2, 10.9, 10.7, 11.4, 16.1) Determine Spearman’s Rho coefficient (2dp) for the following data. x<-c(56,56,65,65,50,25,87,44,35) y<-c(87,91,85,91,75,28,122,66,58)

Please provide your summary on Linear Regression preferably with some code sample in R.

fix this code in python and show me the output. do not change the code import...

fix this code in python and show me the output. do not change the code import random #variables and constants MAX_ROLLS = 5 MAX_DICE_VAL = 6 #declare a list of roll types ROLLS_TYPES = [ "Junk" , "Pair" , "3 of a kind" , "5 of a kind" ] #set this to the value MAX_ROLLS pdice = [0,0,0,0,0] cdice = [0,0,0,0,0] #set this to the value MAX_DICE_VAL pdice = [0,0,0,0,0,0] cdice = [0,0,0,0,0,0] #INPUT - get the dice rolls i...

APPLIED STATISTICS 2 USE R CODE! SHOW R CODE Use data file RecordMath2526.txt, to produce a...

APPLIED STATISTICS 2 USE R CODE! SHOW R CODE Use data file RecordMath2526.txt, to produce a plot graph with Exam1 as x, Exam2 as y, use Gender as color, and Hw1 as pch. RecordMath2526 information Index Gender Hw1 Hw2 Hw3 Exam1 Hw4 Exam2 Hw5 Hw6 Hw7 Final 1 F 9 6 8 60 7 82 10 10 9 69 2 M 10 10 10 94 9 98 10 10 8 91 3 M 9 10 8 79 9 55 10...

Can you give me a reason why to use multiple linear regression and curve fitting in...

Can you give me a reason why to use multiple linear regression and curve fitting in short term load forecasting?

Please answer everything in R programming language. Show the code to me as well. Thank You...

Please answer everything in R programming language. Show the code to me as well. Thank You 1. Problem Open dataset stat500. Package: faraway. Use R (a) Calculate the correlation matrix. 10. (b) Plot total vs hw, to see how strong the relationship. (c) Build a simple linear regression: total regressed against midterm. Print model output. (d) Calculate directly the coefficients as in (3) (e) Calculate the Residual standard error s, as in (4). (f) Calculate the standard error of beta_1,...

The following is a regression summary from R for a linear regression model between an explanatory...

The following is a regression summary from R for a linear regression model between an explanatory variable x and a response variable y. The data contain n = 50 points. Assume that all the conditions for SLR are satisfied. Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.1016 0.4082 -2.699 -------** x 2.2606 0.0981 ---- < 2e-16 *** (a) Write the equation for the least squares regression line. (b) R performs a t-test to test whether the slope is significantly...

Could someone show me how I could create a linear regression model without any intercepts using...

Could someone show me how I could create a linear regression model without any intercepts using Matrix operations. The following points are: (x1, x2, y): (2, 3, 15), (4, 5, 23), (1, 2, 8), and (3, 5, 21).

Linear Regression Regression Statistics R 0.99798 R Square 0.99597 Adjusted R Square 0.99445 Standard Error 1.34247...

Linear Regression Regression Statistics R 0.99798 R Square 0.99597 Adjusted R Square 0.99445 Standard Error 1.34247 Total Number Of Cases 12 Hamb Consump = 176.2709 - 106.6901 * Hamb Price + 4.5651 * Income (1,000s) - 12.1556 * Hot Dog Price ANOVA d.f. SS MS F p-level Regression 3. 3,560.58212 1,186.86071 658.549258 0. Residual 8. 14.41788 1.80224 Total 11. 3,575. Coefficients Standard Error LCL UCL t Stat p-level H0 (5%) rejected? Intercept 176.27093 45.28994 71.83215 280.709717 3.89206 0.0046 Yes Hamb...

Question