Solve for the indicated variable
User Generated
wzttvey1310
Mathematics
Description
C = 2πr ; for r
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
This question has not been answered.
Create a free account to get help with this and any other question!
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!
Most Popular Content
6 pages
Hypothesis Testing Steps.edited
Hypothesis testing is a comprehensive process through which an analysis determines whether sample results, statistics, are ...
Hypothesis Testing Steps.edited
Hypothesis testing is a comprehensive process through which an analysis determines whether sample results, statistics, are significantly different ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, an ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, and justify business predictions based upon the analysis.For this assignment, you will use the "Strength" dataset. You will use SPSS to analyze the dataset and address the questions presented. Findings should be presented in a Word document along with the SPSS outputs.The compressive strength (Y) of concrete is influenced by the mixing proportions and by the time that it is allowed to cure, although the exact relationship between the strength and the components is unknown. The provided data includes the results of n = 1030 concrete strength experiments that include the following:Strength (in MPa): The compressive strength of the concrete.Age (in days): The number of days the concrete was allowed to cured.Coarse_Aggregate (in kg/m3): The proportion of coarse aggregate in the mix.Fine_Aggregate (in kg/m3): The proportion of fine aggregate in the mix.Cement (in kg/m3): The proportion of cement in the mix.Slag (in kg/m3): The proportion of furnace slag in the mix.Superplasticizer (in kg/m3): The proportion of plasticizer in the mix.Water (in kg/m3): The proportion of water in the mix.Ash (in kg/m3): The proportion of fly ash in the mix.Part 1:Derive various transformations of compressive strength to determine which transformation, if any, results in a variable that most closely mimics a normal distribution. To do this, plot Q-Q plots after each transformation listed below, and decide which one should be used to build a multiple linear model. Explain your answer and provide the SPSS output as an illustration.Strength (no transformation)Square root of StrengthSquared Strength(Natural) Log of StrengthReciprocal of StrengthPart 2:Based on the transformation selected in Part 1, build a multiple linear regression model with all eight predictors.Use t-tests to determine if any of the predictors significantly affect the compressive strength of concrete. Explain why each variable should or should not be included in the model. Assume α = 0.05. Show the appropriate model results to explain your answer.If any predictors from question 1 are found to be not significant, remove them and re-run the model to create a reduced model (RM). Are all the remaining variables still statistically significant? Show the appropriate model results to explain your answer.Based on the RM, should there be concern about multicollinearity among the predictors selected? Show the appropriate model results to explain your answer.After fitting the RM, derive the residual plot (standardized residuals vs. standardized predicted values) and normal probability plot. Interpret each plot.What is the coefficient of determination, R2, of the RM? How would you interpret the R2?Based on the RM, what would be the new estimated compressive strength that is currently 50 MPa, after a 10-day increase in curing time? Assume all other predictors are held constant.How would you interpret the intercept (constant) in the RM? Does the interpretation make sense given the data you used to build the RM?Part 3:Given the following components and aging time below, what is the estimated compressive strength based on the RM?Age: 50 daysCoarse_Aggregate: 900 kg/m3Fine_Aggregate: 600 kg/m3Cement: 300 kg/m3Slag: 200 kg/m3Superplasticizer: 7 kg/m3Water: 190 kg/m3Ash: 70 kg/m3Part 4:What is a 95% confidence interval of the estimate in Part 3? How would you interpret the 95% confidence interval? (Hint: Use the SPSS scoring wizard to address this question.)
San Diego City College Using SPSS to Analyze Health Data Project
Using all the information and websites given available. Using SPSS to analyze health data provided. please follow instruct ...
San Diego City College Using SPSS to Analyze Health Data Project
Using all the information and websites given available. Using SPSS to analyze health data provided. please follow instruction provided.
7 pages
Experience89
What are the requirements on sampling and the population so that the distribution of sample means is How do you calculate ...
Experience89
What are the requirements on sampling and the population so that the distribution of sample means is How do you calculate the mean and standard ...
3 pages
Descriptive Statistics
1. Summary of the data and each variable in the data set. The analysis indicates that both the local tuition and foreign t ...
Descriptive Statistics
1. Summary of the data and each variable in the data set. The analysis indicates that both the local tuition and foreign tuition have similar
Similar Content
finding stats probabilities
...
Utah State Dependent Variable in the Democratic Presidential Cand Questions
a simple SPSS exercise that I am struggling greatly on. Will give PDF out to who picks up the question....
USF Social Science Students at USF Statistics Project
I will attach the instructions and rubric and one example of how the paper should look like. I will attach the other files...
Here is the full question
...
Regression class problems
12 True or False questionsyou need to give a clear explanation for why you made the choice that you did. The first questio...
solve and cheek each equation
x + 5 = 0.5...
Control Charts
A control chart is a statistical graph which is used as a tool to monitor changes over a particular period. A control char...
Derivative
...
Solution Confidence Interval
The National Center for Education Statistics surveyed 4400 college graduates about the lengths of time required to earn th...
Related Tags
Book Guides
The Atlantis Gene
by S. A. Beck
Orphan Train
by Christina Baker Kline
The 5 Love Languages
by Gary Chapman
Oliver Twist
by Charles Dickens
How to Win Friends and Influence People
by Dale Carnegie
The Two Towers
by J. R. R. Tolkien
The BFG
by Roald Dahl
Fast Food Nation
by Eric Schlosser
Harry Potter and the Sorcerers Stone
by J. K. Rowling
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
6 pages
Hypothesis Testing Steps.edited
Hypothesis testing is a comprehensive process through which an analysis determines whether sample results, statistics, are ...
Hypothesis Testing Steps.edited
Hypothesis testing is a comprehensive process through which an analysis determines whether sample results, statistics, are significantly different ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, an ...
Multiple regression analysis
The purpose of this assignment is to apply multiple regression concepts, interpret multiple regression analysis models, and justify business predictions based upon the analysis.For this assignment, you will use the "Strength" dataset. You will use SPSS to analyze the dataset and address the questions presented. Findings should be presented in a Word document along with the SPSS outputs.The compressive strength (Y) of concrete is influenced by the mixing proportions and by the time that it is allowed to cure, although the exact relationship between the strength and the components is unknown. The provided data includes the results of n = 1030 concrete strength experiments that include the following:Strength (in MPa): The compressive strength of the concrete.Age (in days): The number of days the concrete was allowed to cured.Coarse_Aggregate (in kg/m3): The proportion of coarse aggregate in the mix.Fine_Aggregate (in kg/m3): The proportion of fine aggregate in the mix.Cement (in kg/m3): The proportion of cement in the mix.Slag (in kg/m3): The proportion of furnace slag in the mix.Superplasticizer (in kg/m3): The proportion of plasticizer in the mix.Water (in kg/m3): The proportion of water in the mix.Ash (in kg/m3): The proportion of fly ash in the mix.Part 1:Derive various transformations of compressive strength to determine which transformation, if any, results in a variable that most closely mimics a normal distribution. To do this, plot Q-Q plots after each transformation listed below, and decide which one should be used to build a multiple linear model. Explain your answer and provide the SPSS output as an illustration.Strength (no transformation)Square root of StrengthSquared Strength(Natural) Log of StrengthReciprocal of StrengthPart 2:Based on the transformation selected in Part 1, build a multiple linear regression model with all eight predictors.Use t-tests to determine if any of the predictors significantly affect the compressive strength of concrete. Explain why each variable should or should not be included in the model. Assume α = 0.05. Show the appropriate model results to explain your answer.If any predictors from question 1 are found to be not significant, remove them and re-run the model to create a reduced model (RM). Are all the remaining variables still statistically significant? Show the appropriate model results to explain your answer.Based on the RM, should there be concern about multicollinearity among the predictors selected? Show the appropriate model results to explain your answer.After fitting the RM, derive the residual plot (standardized residuals vs. standardized predicted values) and normal probability plot. Interpret each plot.What is the coefficient of determination, R2, of the RM? How would you interpret the R2?Based on the RM, what would be the new estimated compressive strength that is currently 50 MPa, after a 10-day increase in curing time? Assume all other predictors are held constant.How would you interpret the intercept (constant) in the RM? Does the interpretation make sense given the data you used to build the RM?Part 3:Given the following components and aging time below, what is the estimated compressive strength based on the RM?Age: 50 daysCoarse_Aggregate: 900 kg/m3Fine_Aggregate: 600 kg/m3Cement: 300 kg/m3Slag: 200 kg/m3Superplasticizer: 7 kg/m3Water: 190 kg/m3Ash: 70 kg/m3Part 4:What is a 95% confidence interval of the estimate in Part 3? How would you interpret the 95% confidence interval? (Hint: Use the SPSS scoring wizard to address this question.)
San Diego City College Using SPSS to Analyze Health Data Project
Using all the information and websites given available. Using SPSS to analyze health data provided. please follow instruct ...
San Diego City College Using SPSS to Analyze Health Data Project
Using all the information and websites given available. Using SPSS to analyze health data provided. please follow instruction provided.
7 pages
Experience89
What are the requirements on sampling and the population so that the distribution of sample means is How do you calculate ...
Experience89
What are the requirements on sampling and the population so that the distribution of sample means is How do you calculate the mean and standard ...
3 pages
Descriptive Statistics
1. Summary of the data and each variable in the data set. The analysis indicates that both the local tuition and foreign t ...
Descriptive Statistics
1. Summary of the data and each variable in the data set. The analysis indicates that both the local tuition and foreign tuition have similar
Earn money selling
your Study Documents