hello
this is about linear regression
i want answer the question using R
write the results and command of R
Homework Answers
Answer -(a)-
here x taken as a dependent variable and y taken as a independent variable run the lm() function in R software for the simple linear regression .Below given the screen shot of R window and define command as well.
Hence using the output data fited model can formed as
y= 91.564 + 32.50x
ANS-(b)
Use the sqrt() command in R to transform the y variable like
![> sqrt (y) [1] 9.899495 11.618950 12.727922 13.341664 14.866069 15.231546 16.822604 [8] 17.320508 19.339080 19.874607](http://img.homeworklib.com/questions/b96d6590-a2a9-11ea-a0a9-91ef8bf52b63.png?x-oss-process=image/resize,w_560)
..................(step-1)(follow this
step for other transformation like log(y)
then use the regression analysis process in the same manner
ANS (c)
when using y coeff of det. = 0.9798 and when taking square root of the y it becames 0.9891 much nearer to 1 since it can say after the transformation model is much precisesly predict the future values and model is good fit.
Ans(d)
put X=12 in each model
eg. in model two Y' = 10.26093+ 1.07629 * 12 = 23.17641
Y^1/2 = 23.17641
then Y = 537.146
Add Answer to:
hello
this is about linear regression
i want answer the question using R
write the results...
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For expert using R , I solve it but i need to figure out what I...
For expert using R , I solve it but i need to figure out what
I got is correct or wrong. Thank you
# Simple Linear Regression and Polynomial Regression
# HW 2
#
# Read data from csv file
data <-
read.csv("C:\data\SweetPotatoFirmness.csv",header=TRUE,
sep=",")
head(data)
str(data)
# scatterplot of independent and dependent variables
plot(data$pectin,data$firmness,xlab="Pectin,
%",ylab="Firmness")
par(mfrow = c(2, 2)) # Split the plotting panel into a 2 x 2
grid
model <- lm(firmness ~ pectin , data=data)
summary(model)
anova(model)
plot(model)...
R is a little difficult for me, please answer if you can interpret the R code, I want to learn better how to interpret the R code 4. each 2 pts] Below is the R output for a simple linear regression m...
R is a little difficult for me, please answer if you can
interpret the R code, I want to learn better how to interpret the R
code
4. each 2 pts] Below is the R output for a simple linear regression model Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 77.863 4.199 18.544 3.54e-13 3.485 3.386 0.00329* 11.801 Signif. codes: 0 0.0010.010.05 0.11 Residual standard error: 3.597 on 18 degrees of freedom Multiple R-squared: 0.3891, Adjusted R-squared: 0.3552 F-statistic: 11.47...
1. For each of the following regression models, write down the X matrix and 3 vector....
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Help & explain please
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This is a question about writting R code for a linear regression
model.
8. . (13 marks) Given four points (1,0.8), (4,4.2), (5,4.7) and (7,7.8), write down your R code to Build the linear regression model. (a) (4 marks) Predict the results on the new data with a sequence of 51 numbers equally spaced (b) values starting from 0 to 8 (4 marks) Generate the plot in Figure 3, where the curved lines are the upper (upr) and lower (c)...
For expert using R , I solve it but i need to figure out what
I got is correct or wrong. Thank you
# Simple Linear Regression and Polynomial Regression
# HW 2
#
# Read data from csv file
data <-
read.csv("C:\data\SweetPotatoFirmness.csv",header=TRUE,
sep=",")
head(data)
str(data)
# scatterplot of independent and dependent variables
plot(data$pectin,data$firmness,xlab="Pectin,
%",ylab="Firmness")
par(mfrow = c(2, 2)) # Split the plotting panel into a 2 x 2
grid
model <- lm(firmness ~ pectin , data=data)
summary(model)
anova(model)
plot(model)...
R is a little difficult for me, please answer if you can
interpret the R code, I want to learn better how to interpret the R
code
4. each 2 pts] Below is the R output for a simple linear regression model Coefficients: Estimate Std. Error t value Pr(>t) (Intercept) 77.863 4.199 18.544 3.54e-13 3.485 3.386 0.00329* 11.801 Signif. codes: 0 0.0010.010.05 0.11 Residual standard error: 3.597 on 18 degrees of freedom Multiple R-squared: 0.3891, Adjusted R-squared: 0.3552 F-statistic: 11.47...
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...
Help & explain please
Regression 1. A researcher is willing to investigate whether there is any linear relation bet ween income (x) in thousand dollars and food expenditures (y) in hundred dollars. A sample data on 7 households given the table below was collected. Assuming that a linear model is used to solve the problem. r-3-D) r-I 83 24 13 61 15 17 1. Write down the linear model 2. Write down the fitted regression line and Interpret the slope...
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