Homework Answers
We have a model with two predictors (Factor A and Factor B) for our response variable. Using a General Linear Model, we have strong R square =97% and Strong Adjusted R square= 96.77%.
Predictors explain 96% of variation in response variable.
Now checking the statistical significance of two factors, we have highly significant p-value for both factors (<0.01). The model is statistically valid for prediction.
Add Answer to:
study on Residuals (40 points). Here are the results of an experiment. Please discuss: (1) what...
P2) A what are the conclusions of this experiment? (2) how adequate is the model proposed...
P2) A what are the conclusions of this experiment? (2) how adequate is the model proposed here to describe the experimental data? (3) any specific problems-if any- that you notice in the residuals? (4) your recommendations about what should be done next in this study case study on Residuals (40 points). Here are the results of an experiment. Please discuss: (1) General Linear Model: Response 2 versus Factor A, Factor B Factor Type Levels Values Factor A fixed Factor B...
Below are given (a) A scatterplot of Y versus X and (b) A plot of residuals...
Below are given (a) A scatterplot of Y versus X and (b) A plot
of residuals versus fitted values after a simple linear regression
model was fit to the data. What is the equation of the fitted line?
Discuss what is indicated about the relationship between Y and X as
it relates to simple linear regression.
Fitted Line Plot Y = - 14.64 + 7.431 X R-Sq R-Sq (adj) 2.43700 91.9% 91.8% 1 > 20- 3 4 5 6 7...
textbook cost is one expense that university students often complain about is the size of the...
textbook cost is one
expense that university students often complain about is the size
of the book( measured by the number of pages) related to the price
of the book( in dollars)
output and the graph
has been posted in the picture.
Q-1 based on the
scatterplot, what can you say about the relationship between pages
and price?
Q-2 state the
regression equation relating predicted price and pages
Q-3 use the regression
equation to find the predicted price y for...
1. The R codes and outputs shown below were obtained from a study of the relationship...
1. The R codes and outputs shown below were obtained from a study of the relationship between heart rate (Y) and the body weight in kg (X). Assume that the linear regres- sion model Y, = Be + Bixi + Ei,i = 1,...,n where €; are i.i.d. N(0,0%) is appropriare for this data. We also assume di's as known constants. > xydata <- read.table("heart.txt", header = TRUE) > fit <- Im(YX, xydata) > summary(fit) Call: 1m(formula = Y - X,...
The first photo is the data I had collected in Minitab.I am confused on what the...
The first photo is the data I
had collected in Minitab.I am confused on what the b1= to then get
the degree of freedom. I need this information to answer question
16 to plug in the right information in minitab to get t*multiplier.
Overall need help with getting the answer to #16 so then I can
continue the rest of the problems. Thanks! (also for 17 what is
S.E.)
Regression: icu versus age Simple Analysis of Variance Source DF Adj...
Yes, as it is in the mint abs. NO: 24,46 so 50 is an outlier (g)...
Yes, as it is in the mint abs. NO: 24,46 so 50 is an outlier (g) Find a 95% confidence interval for the slope. Interpret your confidence interval. (h) Test the null hypothesis that the slope is zero and describe your conclusion. (i) Suppose we wish to predict the mean per capita retail sale for the years with per capita personal income 16000. What is the 95% confidence interval for this prediction? 6) If the per capita personal income in...
4. (20 points) Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to study the relati...
4. (20 points) Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to study the relationship between price and demand for the large bottle of Fresh, the company has gathered data concerning demand for Fresh over the last 30 sales periods. The response variable, demand, is the demand for the large bottle of Fresh (in hundreds of thousands of bottles) in the sales period. The explanatory variable, pricedif, is the average industry price of competitors detergents in...
Scatterplot of PracticeTime vs Age 35 30 Practice Time 25 20 15 5.0 7.5 10.0 12.5...
Scatterplot of PracticeTime vs Age 35 30 Practice Time 25 20 15 5.0 7.5 10.0 12.5 15.0 Age Fitted Line Plot Practice Time = 2.236 + 2.053 Age 35 s R-Sa R-Sqladi) 1.04243 96.7% 96.5% 30 Practice Time 25 20 15 5.0 7.5 10.0 12.5 15.0 Age For children taking piano lessons, we are interested in seeing if there is a relationship between the age of a child (in years) and the amount of time (in minutes) they practice the...
Attached are the results of a diagnostic test on an estimated model, autocorrelation, heteoskedasticity and non-normal...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
Q1 (30 points) Consider Problem 11.45, Page 637. Please note that for this problem the data...
Q1 (30 points) Consider Problem 11.45, Page 637. Please note that for this problem the data will be entered in R as follows: #Enter data on x = Dose Level of Drug, and y = Potency of Drug (Problem 11.45, page 637) x<-c(2, 2, 2, 4, 4, 8, 8, 16, 16, 16, 32, 32, 64, 64, 64) y<-c(5, 7, 3, 10, 14, 15, 17, 20, 21, 19, 23, 29, 28, 31, 30) For this problem, answer the following questions. In...
P2) A what are the conclusions of this experiment? (2) how adequate is the model proposed here to describe the experimental data? (3) any specific problems-if any- that you notice in the residuals? (4) your recommendations about what should be done next in this study case study on Residuals (40 points). Here are the results of an experiment. Please discuss: (1) General Linear Model: Response 2 versus Factor A, Factor B Factor Type Levels Values Factor A fixed Factor B...
Below are given (a) A scatterplot of Y versus X and (b) A plot
of residuals versus fitted values after a simple linear regression
model was fit to the data. What is the equation of the fitted line?
Discuss what is indicated about the relationship between Y and X as
it relates to simple linear regression.
Fitted Line Plot Y = - 14.64 + 7.431 X R-Sq R-Sq (adj) 2.43700 91.9% 91.8% 1 > 20- 3 4 5 6 7...
textbook cost is one
expense that university students often complain about is the size
of the book( measured by the number of pages) related to the price
of the book( in dollars)
output and the graph
has been posted in the picture.
Q-1 based on the
scatterplot, what can you say about the relationship between pages
and price?
Q-2 state the
regression equation relating predicted price and pages
Q-3 use the regression
equation to find the predicted price y for...
1. The R codes and outputs shown below were obtained from a study of the relationship between heart rate (Y) and the body weight in kg (X). Assume that the linear regres- sion model Y, = Be + Bixi + Ei,i = 1,...,n where €; are i.i.d. N(0,0%) is appropriare for this data. We also assume di's as known constants. > xydata <- read.table("heart.txt", header = TRUE) > fit <- Im(YX, xydata) > summary(fit) Call: 1m(formula = Y - X,...
The first photo is the data I
had collected in Minitab.I am confused on what the b1= to then get
the degree of freedom. I need this information to answer question
16 to plug in the right information in minitab to get t*multiplier.
Overall need help with getting the answer to #16 so then I can
continue the rest of the problems. Thanks! (also for 17 what is
S.E.)
Regression: icu versus age Simple Analysis of Variance Source DF Adj...
Yes, as it is in the mint abs. NO: 24,46 so 50 is an outlier (g) Find a 95% confidence interval for the slope. Interpret your confidence interval. (h) Test the null hypothesis that the slope is zero and describe your conclusion. (i) Suppose we wish to predict the mean per capita retail sale for the years with per capita personal income 16000. What is the 95% confidence interval for this prediction? 6) If the per capita personal income in...
4. (20 points) Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to study the relationship between price and demand for the large bottle of Fresh, the company has gathered data concerning demand for Fresh over the last 30 sales periods. The response variable, demand, is the demand for the large bottle of Fresh (in hundreds of thousands of bottles) in the sales period. The explanatory variable, pricedif, is the average industry price of competitors detergents in...
Scatterplot of PracticeTime vs Age 35 30 Practice Time 25 20 15 5.0 7.5 10.0 12.5 15.0 Age Fitted Line Plot Practice Time = 2.236 + 2.053 Age 35 s R-Sa R-Sqladi) 1.04243 96.7% 96.5% 30 Practice Time 25 20 15 5.0 7.5 10.0 12.5 15.0 Age For children taking piano lessons, we are interested in seeing if there is a relationship between the age of a child (in years) and the amount of time (in minutes) they practice the...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
Q1 (30 points) Consider Problem 11.45, Page 637. Please note that for this problem the data will be entered in R as follows: #Enter data on x = Dose Level of Drug, and y = Potency of Drug (Problem 11.45, page 637) x<-c(2, 2, 2, 4, 4, 8, 8, 16, 16, 16, 32, 32, 64, 64, 64) y<-c(5, 7, 3, 10, 14, 15, 17, 20, 21, 19, 23, 29, 28, 31, 30) For this problem, answer the following questions. In...
Most questions answered within 3 hours.
-
1)Which of the following is an
important difference between qualified and nonqualified retirement
plans?
a. Qualified...
asked 1 minute ago -
What's the streaming business's problem on the
horizon?
asked 56 minutes ago -
I need help with writing the conclusion for this online lab
report
Abstract
By testing the...
asked 1 hour ago -
For the reaction 1N2+3H2-----> 2NH3, would the reaction rate
trend be: delta[NH3]/ delta t = -2...
asked 1 hour ago -
Within your current/past organization, identify a problem/issue
and format a design to address same. You may...
asked 1 hour ago -
A sock stuck to the side of a clothes-dryer barrel has a
centripetal acceleration of 24...
asked 2 hours ago -
A perfect gas undergoes an isentropic process such that its
volume doubles. If the ratio of...
asked 2 hours ago -
list the elements in groups 3A to 6A in the same order as in the
periodic...
asked 3 hours ago -
Estimating effect size. Peng and Chen (2014)
evaluated effect size estimates for various tests. In their...
asked 3 hours ago -
Write a script in MySQL that creates and calls a stored
procedure name test. This procedure...
asked 3 hours ago -
If we test the following: H0: μ = 17
vs. H1: μ ≠ 17 and the...
asked 3 hours ago -
in the past year TVG had revenues of 3 million, cost
of goods sold of $25...
asked 3 hours ago