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Communicating Statistical Data Outcomes And Strategic Planning
Selected QIF area is the improvement in data use Stipulates incentives to be given for bestperforming organizations in ...
Communicating Statistical Data Outcomes And Strategic Planning
Selected QIF area is the improvement in data use Stipulates incentives to be given for bestperforming organizations in health records
SNHU Quantitative Analysis Scenario Analysis Stock Options Discussion
InstructionsAs a financial advisor, you are assigned a new client who is considering investing in one of two stocks, A or ...
SNHU Quantitative Analysis Scenario Analysis Stock Options Discussion
InstructionsAs a financial advisor, you are assigned a new client who is considering investing in one of two stocks, A or B.The table below shows information about the performance of stocks A and B last year.
Return
Standard Deviation
Stock A
15 %
8.3%
Stock B
14%
2.1%
As a financial advisor, are there factors other than return and risk that should be considered in making this decision?
Based on these factors, what stock would you recommend to the client?
What reasons will you convey to your client to justify your decision in recommending this stock?
How will this recommendation impact the client?
MTH 154 Northern Virginia Community College Yearly Budget Worksheet
let me know soon as you can yes or no. every thing is there for you of what is needed.
MTH 154 Northern Virginia Community College Yearly Budget Worksheet
let me know soon as you can yes or no. every thing is there for you of what is needed.
ACC 240 Grand Canyon University Coca Cola & PepsiCo Financial Ratios Analysis
The purpose of this assignment is to employ accounting principles and relevant business practices to evaluate a company’ ...
ACC 240 Grand Canyon University Coca Cola & PepsiCo Financial Ratios Analysis
The purpose of this assignment is to employ accounting principles and relevant business practices to evaluate a company’s performance and financial position through a comparison to industry data.
Locate the Critical Thinking CT 10.4 problem at the end of Chapter 10 in the textbook. This will serve as the structure for your assignment. Begin by choosing two competing publicly traded companies from the list below.
Coca-Cola and PepsiCo
Walmart and Target
Nike and Adidas
For the pair of companies selected, you will need to use each company’s stock symbol to locate the liquidity, solvency, and profitability ratios on the MSN Money website. As part of your research, you will need to identify each company’s stock symbol for the American market.
Review the competing companies’ ratios provided at the MSN Money website https://www.msn.com/en-us/moneywww.msn.com . Navigate to My Watchlist and enter the name of the company in the Quote Search. Identify and select the correct stock symbol.
Under the “Analysis” heading, use the Growth, Profitability, Price Ratios, Financial Health, Trading Statistics, and Management Effectiveness information to complete a 750-1,000 word comparison addressing the following:
Evaluate each company’s liquidity relative to its competitor using at least three ratios
Evaluate each company’s solvency relative to its competitor using at least two ratios
Evaluate each company’s profitability relative to its competitor using at least three ratios
Note: You will be assessed on your ability to evaluate each company’s performance based on the information provided at MSN Money. You do not need to calculate the ratios for individual companies or the industry averages.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is located in Course Materials if you need assistance.
Benchmark Information
This benchmark assignment assesses the following programmatic competencies:
BS Secondary Education
5.4: Employ accounting principles and practices relevant to business enterprises.
Spicy Wings Case, statistics homework help
Purpose of Assignment The purpose of this assignment is to develop students' abilities to combine the knowledge of descrip ...
Spicy Wings Case, statistics homework help
Purpose of Assignment The purpose of this assignment is to develop students' abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will develop the ability to use statistical analysis and verify whether or not a claim is valid before advertising it. Assignment Steps Resources: Microsoft Excel®, Spicy Wings Case Study, Spicy Wings Data Set Develop a 700-word statistical analysis. Use descriptive statistics to compute a measure of performance John can use to analyze his delivery performance. Find the following for your measures:MeanStandard deviationSample sizeFive-number summary on the total time Conduct a formal hypothesis testing to help John decide whether to offer the delivery guarantee or not. Estimate the probability of an order taking longer than 30 minutes. Make a recommendation in a short narrative including the following:Based on the sampled data, should John offer the guarantee?What percent of the Saturday deliveries would result in a customer receiving a free order?What recommendations might help John improve his Saturday delivery times?Format your assignment consistent with APA format.
UIUC Statistics Applied and Conceptual Statistics Worksheet
Need Questions Below Answered: Please also use textbook https://hastie.su.domains/ISLR2/ISLRv2_website.pdf for more clear ...
UIUC Statistics Applied and Conceptual Statistics Worksheet
Need Questions Below Answered: Please also use textbook https://hastie.su.domains/ISLR2/ISLRv2_website.pdf for more clear ask. Chapter 4Questions 5,6,7,8,9,12,(13,14,15 - required R code)We now examine the differences between LDA and QDA.(a) If the Bayes decision boundary is linear, do we expect LDA or QDA to perform better on the training set? On the test set?(b) If the Bayes decision boundary is non-linear, do we expect LDA or QDA to perform better on the training set? On the test set?(c) In general, as the sample size n increases, do we expect the test prediction accuracy of QDA relative to LDA to improve, decline, or be unchanged? Why?(d) True or False: Even if the Bayes decision boundary for a given problem is linear, we will probably achieve a superior test er- ror rate using QDA rather than LDA because QDA is flexible enough to model a linear decision boundary. Justify your answer.Suppose we collect data for a group of students in a statistics classwith variables X1 = hours studied, X2 = undergrad GPA, and Y =receive an A. We fit a logistic regression and produce estimated ˆˆˆhas an undergrad GPA of 3.5 gets an A in the class.(b) How many hours would the student in part (a) need to study tohave a 50 % chance of getting an A in the class?7. Suppose that we wish to predict whether a given stock will issue a dividend this year (“Yes” or “No”) based on X, last year’s percent profit. We examine a large number of companies and discover that thēwhile the mean for those that didn’t was X = 0. In addition, the variance of X for these two sets of companies was σˆ2 = 36. Finally, 80 % of companies issued dividends. Assuming that X follows a nor- mal distribution, predict the probability that a company will issue a dividend this year given that its percentage profit was X = 4 last year.Hint: Recall that the density function for a normal random variablecoefficient, β0 = −6, β1 = 0.05, β2 = 1.(a) Estimate the probability that a student who studies for 40 h andmean value of X for companies that issued a dividend was X = 10, ̄1 −(x−μ)2 /2σ2 is f(x) = √2πσ2 e. You will need to use Bayes’ theorem.4.8 Exercises 1918. Suppose that we take a data set, divide it into equally-sized training and test sets, and then try out two different classification procedures.192 4. ClassificationFirst we use logistic regression and get an error rate of 20 % on the training data and 30 % on the test data. Next we use 1-nearest neigh- bors (i.e. K = 1) and get an average error rate (averaged over both test and training data sets) of 18%. Based on these results, which method should we prefer to use for classification of new observations? Why?9. This problem has to do with odds.(a) On average, what fraction of people with an odds of 0.37 ofdefaulting on their credit card payment will in fact default?(b) Suppose that an individual has a 16% chance of defaulting on her credit card payment. What are the odds that she will de- fault?13. This question should be answered using the Weekly data set, which is part of the ISLR2 package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1, 089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010.(a) Produce some numerical and graphical summaries of the Weekly data. Do there appear to be any patterns?(b) Use the full data set to perform a logistic regression with Direction as the response and the five lag variables plus Volume as predictors. Use the summary function to print the results. Do any of the predictors appear to be statistically significant? If so, which ones?(c) Compute the confusion matrix and overall fraction of correct predictions. Explain what the confusion matrix is telling you about the types of mistakes made by logistic regression.(d) Now fit the logistic regression model using a training data period from 1990 to 2008, with Lag2 as the only predictor. Compute the confusion matrix and the overall fraction of correct predictions for the held out data (that is, the data from 2009 and 2010).(e) Repeat (d) using LDA.(f) Repeat (d) using QDA.(g) Repeat (d) using KNN with K = 1.(h) Repeat (d) using naive Bayes.(i) Which of these methods appears to provide the best results on this data?(j) Experiment with different combinations of predictors, includ- ing possible transformations and interactions, for each of the methods. Report the variables, method, and associated confu- sion matrix that appears to provide the best results on the held out data. Note that you should also experiment with values for K in the KNN classifier.4.8 Exercises 193194 4. Classification14. In this problem, you will develop a model to predict whether a given car gets high or low gas mileage based on the Auto data set.(a) Create a binary variable, mpg01, that contains a 1 if mpg contains a value above its median, and a 0 if mpg contains a value below its median. You can compute the median using the median() function. Note you may find it helpful to use the data.frame() function to create a single data set containing both mpg01 and the other Auto variables.(b) Explore the data graphically in order to investigate the associ- ation between mpg01 and the other features. Which of the other features seem most likely to be useful in predicting mpg01? Scat- terplots and boxplots may be useful tools to answer this ques- tion. Describe your findings.(c) Split the data into a training set and a test set.(d) Perform LDA on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(e) Perform QDA on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(f) Perform logistic regression on the training data in order to pre- dict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(g) Perform naive Bayes on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(h) Perform KNN on the training data, with several values of K, in order to predict mpg01. Use only the variables that seemed most associated with mpg01 in (b). What test errors do you obtain? Which value of K seems to perform the best on this data set?15. This problem involves writing functions.(a) Write a function, Power(), that prints out the result of raising 2 to the 3rd power. In other words, your function should compute 23 and print out the results.Hint: Recall that x^a raises x to the power a. Use the print() function to output the result.(b) Create a new function, Power2(), that allows you to pass any two numbers, x and a, and prints out the value of x^a. You can do this by beginning your function with the line> Power2 <- function(x, a) {You should be able to call your function by entering, for instance,> Power2(3, 8)on the command line. This should output the value of 38, namely, 6, 561.(c) Using the Power2() function that you just wrote, compute 103, 17 38 ,and131.(d) Now create a new function, Power3(), that actually returns the result x^a as an R object, rather than simply printing it to the screen. That is, if you store the value x^a in an object called result within your function, then you can simply return() this result, using the following line:return(result)The line above should be the last line in your function, beforethe } symbol.(e) Now using the Power3() function, create a plot of f(x) = x .return()The x-axis should display a range of integers from 1 to 10, and 2the y-axis should display x . Label the axes appropriately, and use an appropriate title for the figure. Consider displaying either the x-axis, the y-axis, or both on the log-scale. You can do this by using log = "x", log = "y", or log = "xy" as arguments to the plot() function.(f) Create a function, PlotPower(), that allows you to create a plot of x against x^a for a fixed a and for a range of values of x. For instance, if you call> PlotPower(1:10, 3)4.8 Exercises 1952then a plot should be created with an x-axis taking on values 3331,2,...,10, and a y-axis taking on values 1 ,2 ,...,10 .
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Most Popular Content
17 pages
Communicating Statistical Data Outcomes And Strategic Planning
Selected QIF area is the improvement in data use Stipulates incentives to be given for bestperforming organizations in ...
Communicating Statistical Data Outcomes And Strategic Planning
Selected QIF area is the improvement in data use Stipulates incentives to be given for bestperforming organizations in health records
SNHU Quantitative Analysis Scenario Analysis Stock Options Discussion
InstructionsAs a financial advisor, you are assigned a new client who is considering investing in one of two stocks, A or ...
SNHU Quantitative Analysis Scenario Analysis Stock Options Discussion
InstructionsAs a financial advisor, you are assigned a new client who is considering investing in one of two stocks, A or B.The table below shows information about the performance of stocks A and B last year.
Return
Standard Deviation
Stock A
15 %
8.3%
Stock B
14%
2.1%
As a financial advisor, are there factors other than return and risk that should be considered in making this decision?
Based on these factors, what stock would you recommend to the client?
What reasons will you convey to your client to justify your decision in recommending this stock?
How will this recommendation impact the client?
MTH 154 Northern Virginia Community College Yearly Budget Worksheet
let me know soon as you can yes or no. every thing is there for you of what is needed.
MTH 154 Northern Virginia Community College Yearly Budget Worksheet
let me know soon as you can yes or no. every thing is there for you of what is needed.
ACC 240 Grand Canyon University Coca Cola & PepsiCo Financial Ratios Analysis
The purpose of this assignment is to employ accounting principles and relevant business practices to evaluate a company’ ...
ACC 240 Grand Canyon University Coca Cola & PepsiCo Financial Ratios Analysis
The purpose of this assignment is to employ accounting principles and relevant business practices to evaluate a company’s performance and financial position through a comparison to industry data.
Locate the Critical Thinking CT 10.4 problem at the end of Chapter 10 in the textbook. This will serve as the structure for your assignment. Begin by choosing two competing publicly traded companies from the list below.
Coca-Cola and PepsiCo
Walmart and Target
Nike and Adidas
For the pair of companies selected, you will need to use each company’s stock symbol to locate the liquidity, solvency, and profitability ratios on the MSN Money website. As part of your research, you will need to identify each company’s stock symbol for the American market.
Review the competing companies’ ratios provided at the MSN Money website https://www.msn.com/en-us/moneywww.msn.com . Navigate to My Watchlist and enter the name of the company in the Quote Search. Identify and select the correct stock symbol.
Under the “Analysis” heading, use the Growth, Profitability, Price Ratios, Financial Health, Trading Statistics, and Management Effectiveness information to complete a 750-1,000 word comparison addressing the following:
Evaluate each company’s liquidity relative to its competitor using at least three ratios
Evaluate each company’s solvency relative to its competitor using at least two ratios
Evaluate each company’s profitability relative to its competitor using at least three ratios
Note: You will be assessed on your ability to evaluate each company’s performance based on the information provided at MSN Money. You do not need to calculate the ratios for individual companies or the industry averages.
Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are required to submit this assignment to LopesWrite. A link to the LopesWrite technical support articles is located in Course Materials if you need assistance.
Benchmark Information
This benchmark assignment assesses the following programmatic competencies:
BS Secondary Education
5.4: Employ accounting principles and practices relevant to business enterprises.
Spicy Wings Case, statistics homework help
Purpose of Assignment The purpose of this assignment is to develop students' abilities to combine the knowledge of descrip ...
Spicy Wings Case, statistics homework help
Purpose of Assignment The purpose of this assignment is to develop students' abilities to combine the knowledge of descriptive statistics covered in Weeks 1 and 2 and one-sample hypothesis testing to make managerial decisions. In this assignment, students will develop the ability to use statistical analysis and verify whether or not a claim is valid before advertising it. Assignment Steps Resources: Microsoft Excel®, Spicy Wings Case Study, Spicy Wings Data Set Develop a 700-word statistical analysis. Use descriptive statistics to compute a measure of performance John can use to analyze his delivery performance. Find the following for your measures:MeanStandard deviationSample sizeFive-number summary on the total time Conduct a formal hypothesis testing to help John decide whether to offer the delivery guarantee or not. Estimate the probability of an order taking longer than 30 minutes. Make a recommendation in a short narrative including the following:Based on the sampled data, should John offer the guarantee?What percent of the Saturday deliveries would result in a customer receiving a free order?What recommendations might help John improve his Saturday delivery times?Format your assignment consistent with APA format.
UIUC Statistics Applied and Conceptual Statistics Worksheet
Need Questions Below Answered: Please also use textbook https://hastie.su.domains/ISLR2/ISLRv2_website.pdf for more clear ...
UIUC Statistics Applied and Conceptual Statistics Worksheet
Need Questions Below Answered: Please also use textbook https://hastie.su.domains/ISLR2/ISLRv2_website.pdf for more clear ask. Chapter 4Questions 5,6,7,8,9,12,(13,14,15 - required R code)We now examine the differences between LDA and QDA.(a) If the Bayes decision boundary is linear, do we expect LDA or QDA to perform better on the training set? On the test set?(b) If the Bayes decision boundary is non-linear, do we expect LDA or QDA to perform better on the training set? On the test set?(c) In general, as the sample size n increases, do we expect the test prediction accuracy of QDA relative to LDA to improve, decline, or be unchanged? Why?(d) True or False: Even if the Bayes decision boundary for a given problem is linear, we will probably achieve a superior test er- ror rate using QDA rather than LDA because QDA is flexible enough to model a linear decision boundary. Justify your answer.Suppose we collect data for a group of students in a statistics classwith variables X1 = hours studied, X2 = undergrad GPA, and Y =receive an A. We fit a logistic regression and produce estimated ˆˆˆhas an undergrad GPA of 3.5 gets an A in the class.(b) How many hours would the student in part (a) need to study tohave a 50 % chance of getting an A in the class?7. Suppose that we wish to predict whether a given stock will issue a dividend this year (“Yes” or “No”) based on X, last year’s percent profit. We examine a large number of companies and discover that thēwhile the mean for those that didn’t was X = 0. In addition, the variance of X for these two sets of companies was σˆ2 = 36. Finally, 80 % of companies issued dividends. Assuming that X follows a nor- mal distribution, predict the probability that a company will issue a dividend this year given that its percentage profit was X = 4 last year.Hint: Recall that the density function for a normal random variablecoefficient, β0 = −6, β1 = 0.05, β2 = 1.(a) Estimate the probability that a student who studies for 40 h andmean value of X for companies that issued a dividend was X = 10, ̄1 −(x−μ)2 /2σ2 is f(x) = √2πσ2 e. You will need to use Bayes’ theorem.4.8 Exercises 1918. Suppose that we take a data set, divide it into equally-sized training and test sets, and then try out two different classification procedures.192 4. ClassificationFirst we use logistic regression and get an error rate of 20 % on the training data and 30 % on the test data. Next we use 1-nearest neigh- bors (i.e. K = 1) and get an average error rate (averaged over both test and training data sets) of 18%. Based on these results, which method should we prefer to use for classification of new observations? Why?9. This problem has to do with odds.(a) On average, what fraction of people with an odds of 0.37 ofdefaulting on their credit card payment will in fact default?(b) Suppose that an individual has a 16% chance of defaulting on her credit card payment. What are the odds that she will de- fault?13. This question should be answered using the Weekly data set, which is part of the ISLR2 package. This data is similar in nature to the Smarket data from this chapter’s lab, except that it contains 1, 089 weekly returns for 21 years, from the beginning of 1990 to the end of 2010.(a) Produce some numerical and graphical summaries of the Weekly data. Do there appear to be any patterns?(b) Use the full data set to perform a logistic regression with Direction as the response and the five lag variables plus Volume as predictors. Use the summary function to print the results. Do any of the predictors appear to be statistically significant? If so, which ones?(c) Compute the confusion matrix and overall fraction of correct predictions. Explain what the confusion matrix is telling you about the types of mistakes made by logistic regression.(d) Now fit the logistic regression model using a training data period from 1990 to 2008, with Lag2 as the only predictor. Compute the confusion matrix and the overall fraction of correct predictions for the held out data (that is, the data from 2009 and 2010).(e) Repeat (d) using LDA.(f) Repeat (d) using QDA.(g) Repeat (d) using KNN with K = 1.(h) Repeat (d) using naive Bayes.(i) Which of these methods appears to provide the best results on this data?(j) Experiment with different combinations of predictors, includ- ing possible transformations and interactions, for each of the methods. Report the variables, method, and associated confu- sion matrix that appears to provide the best results on the held out data. Note that you should also experiment with values for K in the KNN classifier.4.8 Exercises 193194 4. Classification14. In this problem, you will develop a model to predict whether a given car gets high or low gas mileage based on the Auto data set.(a) Create a binary variable, mpg01, that contains a 1 if mpg contains a value above its median, and a 0 if mpg contains a value below its median. You can compute the median using the median() function. Note you may find it helpful to use the data.frame() function to create a single data set containing both mpg01 and the other Auto variables.(b) Explore the data graphically in order to investigate the associ- ation between mpg01 and the other features. Which of the other features seem most likely to be useful in predicting mpg01? Scat- terplots and boxplots may be useful tools to answer this ques- tion. Describe your findings.(c) Split the data into a training set and a test set.(d) Perform LDA on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(e) Perform QDA on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(f) Perform logistic regression on the training data in order to pre- dict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(g) Perform naive Bayes on the training data in order to predict mpg01 using the variables that seemed most associated with mpg01 in (b). What is the test error of the model obtained?(h) Perform KNN on the training data, with several values of K, in order to predict mpg01. Use only the variables that seemed most associated with mpg01 in (b). What test errors do you obtain? Which value of K seems to perform the best on this data set?15. This problem involves writing functions.(a) Write a function, Power(), that prints out the result of raising 2 to the 3rd power. In other words, your function should compute 23 and print out the results.Hint: Recall that x^a raises x to the power a. Use the print() function to output the result.(b) Create a new function, Power2(), that allows you to pass any two numbers, x and a, and prints out the value of x^a. You can do this by beginning your function with the line> Power2 <- function(x, a) {You should be able to call your function by entering, for instance,> Power2(3, 8)on the command line. This should output the value of 38, namely, 6, 561.(c) Using the Power2() function that you just wrote, compute 103, 17 38 ,and131.(d) Now create a new function, Power3(), that actually returns the result x^a as an R object, rather than simply printing it to the screen. That is, if you store the value x^a in an object called result within your function, then you can simply return() this result, using the following line:return(result)The line above should be the last line in your function, beforethe } symbol.(e) Now using the Power3() function, create a plot of f(x) = x .return()The x-axis should display a range of integers from 1 to 10, and 2the y-axis should display x . Label the axes appropriately, and use an appropriate title for the figure. Consider displaying either the x-axis, the y-axis, or both on the log-scale. You can do this by using log = "x", log = "y", or log = "xy" as arguments to the plot() function.(f) Create a function, PlotPower(), that allows you to create a plot of x against x^a for a fixed a and for a range of values of x. For instance, if you call> PlotPower(1:10, 3)4.8 Exercises 1952then a plot should be created with an x-axis taking on values 3331,2,...,10, and a y-axis taking on values 1 ,2 ,...,10 .
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