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A random sample of 5 year old children is evaluated for being left- or right-handed. The size n = 100 children of which 79 ...
Solution
A random sample of 5 year old children is evaluated for being left- or right-handed. The size n = 100 children of which 79 are right-handed, 15 are ...
FIN 701 LSUS Module 4 Financial Management Practical Application Calculations
Practical Application 2 Please see the attachment for questions to be completed This assignment is an opportunity to ...
FIN 701 LSUS Module 4 Financial Management Practical Application Calculations
Practical Application 2 Please see the attachment for questions to be completed This assignment is an opportunity to further practice your time value of money calculation skills and to help reinforce the concepts from this module. Being able to work a wide variety of problem types, and problems with differing setups is important
PUB 550 Grand Canyon University Week 2 Excel and IBM SPSS Statistic Comparative Essay
The purpose of this assignment is to compare basic functions in Excel and SPSS to calculate descriptive statistics and use ...
PUB 550 Grand Canyon University Week 2 Excel and IBM SPSS Statistic Comparative Essay
The purpose of this assignment is to compare basic functions in Excel and SPSS to calculate descriptive statistics and use this information to describe the sample.For this assignment, students will utilize Excel with the Data Analysis ToolPak and SPSS Statistics and the "Example Dataset" to complete the assignment. Refer to the Topic Materials for assistance with enabling the Data Analysis ToolPak on a Mac or PC.Part 1:Complete the following steps in both Excel and IBM SPSS Statistics.Calculate mean, median, and mode for the variables "Annual Income" and "Age." Show the appropriate summary tables for these measures from both Excel and SPSS. Include the other descriptive statistics that are a part of the summary output in Excel and SPSS.Create histograms to show the distribution for "Annual Income" and "Age." Copy and paste the histograms from Excel and export the histogram from SPSS into the Word document for this assignment.Create frequency tables that include counts and percentages for smoking status, employment status, exercise level, and education level. Show the tables in the Word document for this assignment.Part 2:Based upon the Part 1 activities, write a 250-500 word interpretation that addresses the following.Discuss the sampling strategy used in this study and if it resulted in a representative sample.Discuss what you are able to ascertain about the sample from the descriptive statistics.Explain what other variables the research team could have included to gain a better understanding of the population.General RequirementsSubmit one Word document for the Part 1 assignment content and a second Word document for Part 2 of the assignment.APA style is not required, but solid academic writing is expected.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for ...
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.Define the question your report is trying to answer.Explain when using linear regression is most appropriate.When using linear regression, what would you expect the scatterplot to look like?Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.Data CollectionSampling the data: Select a random sample of 50 houses.Identify your response and predictor variables.Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables.Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.Explain if a regression model is appropriate to develop based on your scatterplot.Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.Find r: Find the correlation coefficient (r).Explain how the r value you calculated supports what you noticed in your scatterplot.Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.Determine the strength of the linear regression equation you developed.Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.Did you see the results you expected, or was anything different from your expectations or experiences?What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.
19 pages
Major Assignment 2 Completed
You have entered your full name in the field provided. The interest rates you have entered come from the mortgage rates ta ...
Major Assignment 2 Completed
You have entered your full name in the field provided. The interest rates you have entered come from the mortgage rates table and
MIS 445 Business Statistics Project
R is a free statistical software that is frequently and widely used. Go to R-Project for Statistical Computing (Link ...
MIS 445 Business Statistics Project
R is a free statistical software that is frequently and widely used. Go to R-Project for Statistical Computing (Links to an external site.)Links to an external site. to download the R software to your computer (follow the instructions provided in the attached R Installation Instructions sheet). The R Project website (Links to an external site.)Links to an external site. provides a brief introduction to R that you may also want to review.
n this CT assignment, we will use R software to analyze a dataset GoogleAmazonStock.xlsx.
It contains daily closing stock prices for Google and Amazon from 8/22/2017 to 8/22/2018. When we examine stock prices (or other financial assets) we often transform them into a (simple) return series. The return series are computed by the formula: (present price/past price) - 1. The dataset contains both stock prices and return series.
1. Using R, construct time series (line) plots for both stock prices and return series. R functions ts.plot or plot can create the plot. Describe the patterns and compare the plots.
2. Based on the return series, can we claim that the mean Amazon return series is higher than that of Google?
a. What would be an appropriate test of the claim above? Explain.
b. Write the null and alternative hypotheses.
c. Using R, perform the test.
d. Write the decision in the problem context.
Take the screenshots of the R graphs and output as well as the code. Paste them into a Word document along with your answers to the questions above. Clearly label the questions and answers. Submit the Word file in Canvas.
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Most Popular Content
6 pages
Solution
A random sample of 5 year old children is evaluated for being left- or right-handed. The size n = 100 children of which 79 ...
Solution
A random sample of 5 year old children is evaluated for being left- or right-handed. The size n = 100 children of which 79 are right-handed, 15 are ...
FIN 701 LSUS Module 4 Financial Management Practical Application Calculations
Practical Application 2 Please see the attachment for questions to be completed This assignment is an opportunity to ...
FIN 701 LSUS Module 4 Financial Management Practical Application Calculations
Practical Application 2 Please see the attachment for questions to be completed This assignment is an opportunity to further practice your time value of money calculation skills and to help reinforce the concepts from this module. Being able to work a wide variety of problem types, and problems with differing setups is important
PUB 550 Grand Canyon University Week 2 Excel and IBM SPSS Statistic Comparative Essay
The purpose of this assignment is to compare basic functions in Excel and SPSS to calculate descriptive statistics and use ...
PUB 550 Grand Canyon University Week 2 Excel and IBM SPSS Statistic Comparative Essay
The purpose of this assignment is to compare basic functions in Excel and SPSS to calculate descriptive statistics and use this information to describe the sample.For this assignment, students will utilize Excel with the Data Analysis ToolPak and SPSS Statistics and the "Example Dataset" to complete the assignment. Refer to the Topic Materials for assistance with enabling the Data Analysis ToolPak on a Mac or PC.Part 1:Complete the following steps in both Excel and IBM SPSS Statistics.Calculate mean, median, and mode for the variables "Annual Income" and "Age." Show the appropriate summary tables for these measures from both Excel and SPSS. Include the other descriptive statistics that are a part of the summary output in Excel and SPSS.Create histograms to show the distribution for "Annual Income" and "Age." Copy and paste the histograms from Excel and export the histogram from SPSS into the Word document for this assignment.Create frequency tables that include counts and percentages for smoking status, employment status, exercise level, and education level. Show the tables in the Word document for this assignment.Part 2:Based upon the Part 1 activities, write a 250-500 word interpretation that addresses the following.Discuss the sampling strategy used in this study and if it resulted in a representative sample.Discuss what you are able to ascertain about the sample from the descriptive statistics.Explain what other variables the research team could have included to gain a better understanding of the population.General RequirementsSubmit one Word document for the Part 1 assignment content and a second Word document for Part 2 of the assignment.APA style is not required, but solid academic writing is expected.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for ...
Southern New Hampshire University Statistics Worksheet
ScenarioYou have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.DirectionsUsing the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis.Note: Present your data in a clearly labeled table and using clearly labeled graphs.Specifically, include the following in your report:IntroductionDescribe the report: Give a brief description of the purpose of your report.Define the question your report is trying to answer.Explain when using linear regression is most appropriate.When using linear regression, what would you expect the scatterplot to look like?Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.Data CollectionSampling the data: Select a random sample of 50 houses.Identify your response and predictor variables.Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model.Data AnalysisHistogram: For your two variables, create histograms.Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.Interpret the graphs and statistics:Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables.Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales?Develop Your Regression ModelScatterplot: Provide a graph of the scatterplot of the data with a line of best fit.Explain if a regression model is appropriate to develop based on your scatterplot.Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.Identify any possible outliers or influential points and discuss their effect on the correlation.Discuss keeping or removing outlier data points and what impact your decision would have on your model.Find r: Find the correlation coefficient (r).Explain how the r value you calculated supports what you noticed in your scatterplot.Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.Interpret regression equation: Interpret the slope and intercept in context.Strength of the equation: Provide and interpret R-squared.Determine the strength of the linear regression equation you developed.Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home.ConclusionsSummarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.Did you see the results you expected, or was anything different from your expectations or experiences?What changes could support different results, or help to solve a different problem?Provide at least one question that would be interesting for follow-up research.You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.
19 pages
Major Assignment 2 Completed
You have entered your full name in the field provided. The interest rates you have entered come from the mortgage rates ta ...
Major Assignment 2 Completed
You have entered your full name in the field provided. The interest rates you have entered come from the mortgage rates table and
MIS 445 Business Statistics Project
R is a free statistical software that is frequently and widely used. Go to R-Project for Statistical Computing (Link ...
MIS 445 Business Statistics Project
R is a free statistical software that is frequently and widely used. Go to R-Project for Statistical Computing (Links to an external site.)Links to an external site. to download the R software to your computer (follow the instructions provided in the attached R Installation Instructions sheet). The R Project website (Links to an external site.)Links to an external site. provides a brief introduction to R that you may also want to review.
n this CT assignment, we will use R software to analyze a dataset GoogleAmazonStock.xlsx.
It contains daily closing stock prices for Google and Amazon from 8/22/2017 to 8/22/2018. When we examine stock prices (or other financial assets) we often transform them into a (simple) return series. The return series are computed by the formula: (present price/past price) - 1. The dataset contains both stock prices and return series.
1. Using R, construct time series (line) plots for both stock prices and return series. R functions ts.plot or plot can create the plot. Describe the patterns and compare the plots.
2. Based on the return series, can we claim that the mean Amazon return series is higher than that of Google?
a. What would be an appropriate test of the claim above? Explain.
b. Write the null and alternative hypotheses.
c. Using R, perform the test.
d. Write the decision in the problem context.
Take the screenshots of the R graphs and output as well as the code. Paste them into a Word document along with your answers to the questions above. Clearly label the questions and answers. Submit the Word file in Canvas.
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