Posted: July 31st, 2022
Chapter 1: An Introduction to Business Statistics
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
Chapter 3: Descriptive Statistics: Numerical Methods
Performance Report. You are the manager at a company and are asked to present a report on the year-to-date performance of your division. What type of statistical information would you include in your report? In particular, which descriptive statistics (mean, median, standard deviation, etc.) do you think would best represent the main aspects of the performance of your division? What types of graphical presentation (histogram, dot plot, stem-and-leaf, bar chart, etc.) would you include? Explain your reasoning.
The Empirical Rule vs. Chebyshev’s Theorem. Discuss how the Empirical Rule works and how it relates to the bell curve as illustrated in Figure 3.14 (a). Then, explain Chebyshev’s Theorem and how it is different from the Empirical Rule. Give a specific example of a population with which the Empirical Rule might be most effective and one with which Chebyshev’s Theorem might be most effective.
1. Due Day 6. Week One Quiz. Complete the quiz on the assigned readings for the week.
Week One Problems. Complete the following problems from the textbook and submit them as a Word file.
Chapter 1: 1.2, 1.17
Chapter 3: 3.3, 3.22
Chapter 4: Probability
Chapter 5: Discrete Random Variables
Chapter 6: Continuous Random Variables
Relative Frequency. Conceptually we would expect the probability of newborn males and females to be the same. However, census reports indicate that the ratios of males and females in various countries do not conform to the theoretical prediction. What do you think accounts for this variation? Can you think of other cases where the expected probabilities do not quite agree with the empirical values?
Applications for Probability. In what situations might you use probability as a manager to approach business-related problems? What are the advantages to using probability concepts in business decisions? Are there any disadvantages or possible pitfalls to avoid in using probability in business?
1. Due Day 6. Week Two Quiz. Complete the quiz on the assigned readings for the week.
Week Two Problems. Complete the following problems from the textbook and submit them as a Word file. When appropriate, you may use either Excel or Megastat to complete (see tutorials in chapter appendices).
Chapter 4: 4.4, 4.20, 5.12, 6.22(a)
Chapter 7: Sampling and Sampling Distributions
Chapter 8: Confidence Intervals
Unscientific Sampling. Consider question 7.45 from the text: A Milwaukee television station, WITI-TV, conducted a telephone call-in survey asking whether viewers liked the new newspaper, the Journal Sentinel. On April 26, 1995, Tim Cuprisin, a columnist for the Journal Sentinel, wrote the following comment: “WITI-TV (Channel 6) did one of those polls—which they admit are unscientific—last week and found that 388 viewers like the new Journal Sentinel and 2,629 didn’t like it. We did our own unscientific poll on whether those Channel 6 surveys accurately reflect public opinion. The results: a full 100 percent of the respondents say absolutely, positively not.”
Is Cuprisin’s comment justified?
Article Review. Many articles present statistical data and list margins of error (for example, reports on political opinion polls, growth or decline of the housing markets, manufacturing sectors, etc.). Find one such article from a reliable source (such as EBSCO or Proquest) in the online library that includes a construction of confidence intervals for the data studied, and give a summary of the topic and the statistical results presented. In particular, discuss whether there is enough information presented in the article to arrive at the same conclusion as reported.
1. Due Day 6. Week Three Quiz. Complete the quiz on the assigned readings for the week.
Week Three Problems. Complete the following problems from the textbook and submit them as a Word file. When appropriate, you may use either Excel or Megastat to complete (see tutorials in chapter appendices).
Chapter 7: 7.11, 7.30, 8.8, 8.38
1. Chapter 9: Hypothesis Testing
2. Chapter 12: Chi-Square Tests
Hypothesis Test. Give an example of a hypothesis test you could perform at work or at home. State what the Null and the Alternative hypotheses would be in your test. Explain how you would settle on a reasonable level of significance for your scenario. Also explain what the type I and II errors would be if you reached the incorrect conclusion in your test.
Creating Hypotheses. Assume you are the manager of a paint manufacturing factory. Your company has received complaints from customers that the containers hold less than the amount printed on them. On the other hand, corporate management is concerned that the containers hold more than the standard amount. You assign a statistician to verify these claims. A sample of containers was selected and the volume of paint in each container was measured. Assuming that the volume printed on each container is 1 gallon, how would you formulate the null and alternative hypotheses to test the customers’ claim? As a manager, what reasonable criteria will you use to set a value for the level of significance to be used in the test? After answering this question, what type of error would you suppose may result in that case?
1. Due Day 6. Week Four Quiz. Complete the quiz on the assigned readings for the week.
Week Four Problems. Complete the following problems from the textbook and submit them as a Word file. When appropriate, you may use either Excel or Megastat to complete (see tutorials in chapter appendices).
Chapter 9: 9.13, 9.22
Chapter 12: 12.10, 12.18(a)
1. Chapter 13: Simple Linear Regression Analysis
2. Chapter 15: Process Improvement Using Control Charts (on textbook website: http://highered.mcgraw-hill.com/sites/007340182x/student_view0/chapter_15.html)
Linear Correlation. Do you think there is a correlation between CEO salaries and the degree of success of a company? If you were to take a sample of companies with comparable size, market capitalization, and product category, and plot CEO salaries against the net profit of their respective companies, do you expect to find a linear correlation between the two? Explain.
Quality Control. Visit the websites on Quality Control (QC) listed in the Required Websites for this week. In addition, locate an article on the Internet or in the Library databases that describes an example of the use of statistics in Quality Control. In your post, briefly define Quality Control and explain its importance. Also, describe some of the most widely used tools in the industry for measuring and controlling quality, emphasizing their relationship to what you have encountered in this class. Finally, explain the example from your article of statistics as applied in a Quality Control context.
Focus of the Final Project
To complete this project, use the “Final Project Data Set” found in your eCollege classroom in the Final Project description.
1. Calculate the mean yearly value using the average gas prices by month found in the “Final Project Data Set.”
2. Using the years as your x-axis and the annual mean as your y-axis, create a scatterplot and a linear regression line.
3. Answer the following questions using your scatterplot and linear regression line:
a. What is the slope of the linear regression line?
b. What is the Y-intercept of the linear regression line?
c. What is the equation of the linear regression line in slope-intercept form?
d. Based on the linear regression line, what would be an estimated cost of gas in the year 2020?
e. What are the residuals of each year?
f. Select a current price that you have seen or paid recently for gas. Is that price within the range of the linear regression line or is it an outlier? Is it within the confidence interval of 5% or either end?
Imagine that you are a manager at a delivery service and you are creating a report to project the effects on your company of rising gas prices in the next ten years. Using the preceding statistical analysis as your basis and outside scholarly resources to support your claims, write a 3 to 5 page paper interpreting the results from this perspective. Include the following considerations:
1. Introduce the project and its significance to the company.
2. Explain the statistical analysis that you completed in Part I. Be sure to explain where the data came from, what analysis was done, and what the results were.
3. Give conclusions that you have drawn from the data. Consider the effects of your gas price predictions on the delivery business. Also consider whether or not you believe your predicted gas prices are accurate. What could occur in the future that would change your linear regression line and therefore your prediction?
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