During the global recession of 2008 and 2009, there were many accusations of une

by | Aug 1, 2022 | Math

During the global recession of 2008 and 2009, there were many accusations of unethical behavior by Wall Street executives, financial managers, and other corporate officers. At that time, an article appeared that suggested that part of the reason for such unethical business behavior may have stemmed from the fact that cheating had become more prevalent among business students, according to a February 10, 2009, article in the Chronicle of Higher Education. The article reported that 56% of business students admitted to cheating at some time during their academic career as compared to 47% of nonbusiness students. Cheating has been a concern of the dean of the college of business at Bo Diddley Tech (BDT) for several years. Some faculty members in the college believe that cheating is more widespread at BDT than at other universities, whereas other faculty members think that cheating is not a major problem in the college. To resolve some of these issues, the dean commissioned a study to assess the current ethical behavior of business students at BDT. As a former college athlete herself, the dean believed that the spirit of fair play students develop as part of participating in athletics would make them less likely to cheat. As part of this study, an anonymous exit survey was administered to a sample of 240 students from this year’s graduating class, half of whom were business students and half of whom were not. The survey asked various questions, including the student’s college and if the student was an athlete or not. Responses of the various questions were fed into a computer algorithm that made a quantitative determination as to whether the student should be considered a “cheater” or not. The results are in the attached Excel spreadsheet, “Benchmark – Bo Diddley Tech Data Set.” Prepare a managerial report as part of your submission to the dean of the college that summarizes your assessment of the nature of cheating at BDT. Be sure to include the following items in your written report.

In this project, you will demonstrate your mastery of the following competencies

by | Aug 1, 2022 | Math

In this project, you will demonstrate your mastery of the following competencies: Apply statistical techniques to address research problems Perform regression analysis to address an authentic problem Overview The purpose of this project is to have you complete all of the steps of a real-world linear regression research project starting with developing a research question, then completing a comprehensive statistical analysis, and ending with summarizing your research conclusions. Scenario You 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. Directions Using 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: Introduction Describe 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 Collection Sampling 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 Analysis Histogram: 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 Model Scatterplot: 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. Conclusions Summarize 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.

All work needs to be completed by the morning of July 31st, 2021 EST Time. The m

by | Jul 31, 2022 | Math

All work needs to be completed by the morning of July 31st, 2021 EST Time. The module homework assignment needs to be completed first. After the module homework assignment is completed then the quiz is next, the quiz is on modules 6 and 7. Both module lesson plans and lesson questions will be able to be viewed prior to taking the quiz.

YOU WILL BE COMPLETING 4 ASSIGNMENTS WHICH ARE ALL GRADED. YOU MUST GET SCORES A

by | Jun 24, 2022 | Math

YOU WILL BE COMPLETING 4 ASSIGNMENTS WHICH ARE ALL GRADED. YOU MUST GET SCORES ABOVE 80% AND IF YOU DON’T YOU HAVE TO REDO IT. BUT MOST IMPORTANTLY IS THAT THEY MUST BE DONE TODAY. RECENTLY I HAVE ENCOUNTERED MULTIPLE TUTORS ON THIS WEBSITE THAT TRIED GETTING AWAY WITH BAD WORK AND COMPLETELY MISSING THE DUE DATE. I WAS ABLE TO GET THEM REMOVED FROM THIS SITE FOR THEFT.

The modules are simple interest and compound interest, Ordinary Annuities, Annui

by | Jun 20, 2022 | Math

The modules are simple interest and compound interest, Ordinary Annuities, Annuities-payment size, term, and interest rate, Deferred Annuities and perpetuities, Amortization of loans and mortgages, and lastly Bonds and sinking funds. The top three modules are completed which are simple, compound, and ordinary. But you should know for the test and assignment