The answer is the third one,
can it be explained as to why please
Homework Answers
M[,2] will extract all rows and 2nd column from matrix M
[1] will get first element
M[,2][1] will give first element of second column
so as in the above question.
info$coeffieints[,2] is Std. error column
Add Answer to:
The answer is the third one,
can it be explained as to why please
You run...
The data set "mtcars" in R has 11 variables with 32 observations. A data frame with...
The data set "mtcars" in R has 11 variables with 32 observations. A data frame with 32 observations on 11 variables. [, 1] mpg Miles/(US) gallon [, 2] cyl Number of cylinders [, 3] disp Displacement (cu.in.) [, 4] hp Gross horsepower [, 5] drat Rear axle ratio [, 6] wt Weight (1000 lbs) [, 7] qsec 1/4 mile time [, 8] vs V/S [, 9) am Transmission (0 = automatic, 1 = manual) [,10] gear Number of forward gears...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the linear regression output below and answer the following questions Results of linear regression analysis are shown below: Call: lm (formula = mpg ~ ., data = auto-mpg) Residuals: Min 1Q Median 3Q Max -8.6927-2.3864 -0.0801 2.0291 14.3607 Coefficients: Estimate Std. Error t value Pr>Itl) (Intercept) -1.454e+01 4.764e+00 -3.051 0.00244* cyl disp hp gvw accel year -3.299e-01 3.321e-01 -0.993 0.32122 7.678e-03 7.358e-03 1.044 0.29733 -3.914e-04...
please show your explanation thanks! ## ## Call: ## Im(formula = mpg ~ disp + hp...
please show your explanation thanks!
## ## Call: ## Im(formula = mpg ~ disp + hp + wt + osec, data = mtcars.train.df) ## ## Residuals: Min 1Q Median ## -4.3442 -1.1687 -0.4033 3Q Max 1.0519 5.9623 ## ## Coefficients: Estimate Std. Error t value Pr>t) ## (Intercept) 31.204891 10.909916 2.860 0.00967 ** ## disp 0.009432 0.012308 0.766 0.45245 ## hp -0.032908 0.025528 -1.289 0.21208 ## wt -4.978374 1.434757 -3.470 0.00242 ** ## qsec 0.434043 0.576267 0.753 0.46011 ## ---...
PLEASE ANSWER ALL parts . IF YOU CANT ANSWER ALL, KINDLY ANSWER PART (E) AND PART(F)...
PLEASE ANSWER ALL parts .
IF YOU CANT ANSWER ALL, KINDLY ANSWER PART (E) AND
PART(F)
FOR PART (E) THE REGRESSION MODEL IS ALSO GIVE AT THE
END.
REGRESSION MODEL:
We will be returning to the mtcars dataset, last seen in assignment 4. The dataset mtcars is built into R. It was extracted from the 1974 Motor Trend US magazine, and comcaprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models). You can find...
2. What is the coefficient of correlation between miles per gallon and weight? What is the...
2. What is the coefficient of correlation between miles per gallon and weight? What is the sign of the correlation coefficient? Does the coefficient of correlation indicate a strong correlation, weak correlation, or no correlation between the two variables? How do you know? See Step 3 in the Python script. 3. Write the simple linear regression equation for miles per gallon as the response variable and weight as the predictor variable. How might the car rental company use this model?...
> ml < lm(grad.rate-Average.loans+SAT.reading.25p+SAT.math.25p+SFR +sector,data-ouryearipeda) sum...
> ml < lm(grad.rate-Average.loans+SAT.reading.25p+SAT.math.25p+SFR +sector,data-ouryearipeda) summary (ml) Call: Im(formulagrad.rateAverage.loansSAT.reading.25p SAT.math.25p SFR +sector, data-fouryearipeda.) Residuals: -54.768 -6.150 0.596 6.601 38.514 Coefficients: Min 1Q Median 3Q Max Estimate Std. Error t value Pr>ltl) -4.331e+01 3.046e+00 -14.221 <2e-16 (Intercept) Average.loans SAT.reading.25p SAT.math.25p SFR sectorPublic, 4-year or above -2.602e+00 7.907e-01 -3.291 0.00103* .573e-03 1.963e-04 8.011 2.77e-15 8.455e-02 1.178e-02 7.177 1.27e-12* 1.086e-01 1.072e-02 10.138 <2e-16 -1.812e-01 9.119e-02 -1.988 0.04710 Residual standard error: 9.855 on 1149 degrees of freedom (1219 observations deleted due toniAnǐngnes Multiple R-squared:...
please answer question 7 (confidence interval). (14 points) Birth weight and gestational age. The Child Health...
please answer question 7 (confidence interval).
(14 points) Birth weight and gestational age. The Child Health and Development Studies considered pregnancies among women in the San Francisco East Bay area. Researchers took a random sample of 50 pregnancies and used statistical software to construct a linear regression model to predict a baby's birth weight in ounces using the gestation age (the number of days the mother was pregnant). A portion of the computer output and the scatter plot is shown...
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...
The R code will help to answer the question. 8. DeGroot&Shervish (2002) consider an experiment to...
The R code will help to answer
the question.
8. DeGroot&Shervish (2002) consider an experiment to study the combined effects of taking a stimulant and a tranquilizer. In this experiment three types of stimulant and four types of tranquilizer are administered to a group of rabbits. Each rabbit received one of the stimulants, then 20 minutes later, one of the tranquilizers. One hour later their response time (in microseconds) to a stimulus was measured. The results were: Tranquilizer Stimulant 1...
Use the following regression output from R studio and answer the following questions. 1. Comment on...
Use the following regression output from R studio and answer the
following questions.
1. Comment on the relation between the two test marks.
A. There appears to be no linear relation between the
two test marks
B. There appears to be strong negative linear relation between the
two test marks.
C. There appears to be weak positive linear relation between the
two test marks.
D. There appears to be strong positive linear relation
between the two test marks.
2. If the linear...
The data set "mtcars" in R has 11 variables with 32 observations. A data frame with 32 observations on 11 variables. [, 1] mpg Miles/(US) gallon [, 2] cyl Number of cylinders [, 3] disp Displacement (cu.in.) [, 4] hp Gross horsepower [, 5] drat Rear axle ratio [, 6] wt Weight (1000 lbs) [, 7] qsec 1/4 mile time [, 8] vs V/S [, 9) am Transmission (0 = automatic, 1 = manual) [,10] gear Number of forward gears...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the linear regression output below and answer the following questions Results of linear regression analysis are shown below: Call: lm (formula = mpg ~ ., data = auto-mpg) Residuals: Min 1Q Median 3Q Max -8.6927-2.3864 -0.0801 2.0291 14.3607 Coefficients: Estimate Std. Error t value Pr>Itl) (Intercept) -1.454e+01 4.764e+00 -3.051 0.00244* cyl disp hp gvw accel year -3.299e-01 3.321e-01 -0.993 0.32122 7.678e-03 7.358e-03 1.044 0.29733 -3.914e-04...
please show your explanation thanks!
## ## Call: ## Im(formula = mpg ~ disp + hp + wt + osec, data = mtcars.train.df) ## ## Residuals: Min 1Q Median ## -4.3442 -1.1687 -0.4033 3Q Max 1.0519 5.9623 ## ## Coefficients: Estimate Std. Error t value Pr>t) ## (Intercept) 31.204891 10.909916 2.860 0.00967 ** ## disp 0.009432 0.012308 0.766 0.45245 ## hp -0.032908 0.025528 -1.289 0.21208 ## wt -4.978374 1.434757 -3.470 0.00242 ** ## qsec 0.434043 0.576267 0.753 0.46011 ## ---...
PLEASE ANSWER ALL parts .
IF YOU CANT ANSWER ALL, KINDLY ANSWER PART (E) AND
PART(F)
FOR PART (E) THE REGRESSION MODEL IS ALSO GIVE AT THE
END.
REGRESSION MODEL:
We will be returning to the mtcars dataset, last seen in assignment 4. The dataset mtcars is built into R. It was extracted from the 1974 Motor Trend US magazine, and comcaprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models). You can find...
2. What is the coefficient of correlation between miles per gallon and weight? What is the sign of the correlation coefficient? Does the coefficient of correlation indicate a strong correlation, weak correlation, or no correlation between the two variables? How do you know? See Step 3 in the Python script. 3. Write the simple linear regression equation for miles per gallon as the response variable and weight as the predictor variable. How might the car rental company use this model?...
> ml < lm(grad.rate-Average.loans+SAT.reading.25p+SAT.math.25p+SFR +sector,data-ouryearipeda) summary (ml) Call: Im(formulagrad.rateAverage.loansSAT.reading.25p SAT.math.25p SFR +sector, data-fouryearipeda.) Residuals: -54.768 -6.150 0.596 6.601 38.514 Coefficients: Min 1Q Median 3Q Max Estimate Std. Error t value Pr>ltl) -4.331e+01 3.046e+00 -14.221 <2e-16 (Intercept) Average.loans SAT.reading.25p SAT.math.25p SFR sectorPublic, 4-year or above -2.602e+00 7.907e-01 -3.291 0.00103* .573e-03 1.963e-04 8.011 2.77e-15 8.455e-02 1.178e-02 7.177 1.27e-12* 1.086e-01 1.072e-02 10.138 <2e-16 -1.812e-01 9.119e-02 -1.988 0.04710 Residual standard error: 9.855 on 1149 degrees of freedom (1219 observations deleted due toniAnǐngnes Multiple R-squared:...
please answer question 7 (confidence interval).
(14 points) Birth weight and gestational age. The Child Health and Development Studies considered pregnancies among women in the San Francisco East Bay area. Researchers took a random sample of 50 pregnancies and used statistical software to construct a linear regression model to predict a baby's birth weight in ounces using the gestation age (the number of days the mother was pregnant). A portion of the computer output and the scatter plot is shown...
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...
The R code will help to answer
the question.
8. DeGroot&Shervish (2002) consider an experiment to study the combined effects of taking a stimulant and a tranquilizer. In this experiment three types of stimulant and four types of tranquilizer are administered to a group of rabbits. Each rabbit received one of the stimulants, then 20 minutes later, one of the tranquilizers. One hour later their response time (in microseconds) to a stimulus was measured. The results were: Tranquilizer Stimulant 1...
Use the following regression output from R studio and answer the
following questions.
1. Comment on the relation between the two test marks.
A. There appears to be no linear relation between the
two test marks
B. There appears to be strong negative linear relation between the
two test marks.
C. There appears to be weak positive linear relation between the
two test marks.
D. There appears to be strong positive linear relation
between the two test marks.
2. If the linear...
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