BUSN 5760 Applied Business Statistics

The student examines the application of statistical analysis, hypothesis testing, and regression analysis in business decision making.  The course should focus on the utililization of statistical methods as applied to business problems and operations.

Students should have had previous graduate or undergraduate courses in economics and statistics.  Knowledge of basic algebra is required.

1)         Provide students with a strong background in statistics;

2)         Enable students to determine how to interpret statistical information;

3)         Enable students to master the use of statistical software or a statistical calculator to help inform business decisions; and

4)         Enable students to experience using statistical analysis as a means to develop solutions to problems.

 

Notes: 

1)         Objective 1 is the culmination of the course.  Through the lectures, discussions, homework assignments, and exams, the students will gain a strong background and understanding in statistics.  Students will be able to: 

•           Evaluate business decisions by use of ordinary and business statistics.

•           Define and know when to use the proper measure of central tendency and the four levels of measurements.

•           Perform a statistical analysis using both hypothesis and confidence interval tests and properly interpret the results.

•           Demonstrate the use and interpretation of a one-way ANOVA test.

•           Demonstrate the proper use of linear regression techniques for business forecasting.

•           Describe the differences between quantitative and qualitative data and apply the proper analytical techniques for each.

 

2)         Objective 2 is accomplished through the current event assignment, course project, and portions of the problems sets.  Each student is required to present one current event related to statistics to the class during the course.  They must also write a one page summary of the article and how it relates to statistics.  In week 2, students are assigned a course project that will require the students to located data, describe the variables, conduct statistical procedures, and summarize the findings.  In addition, each week, the students are assigned problems from the chapters that were discussed.  The students are required in these assignments to interpret and discuss the statistical findings of the article, project, or problem. 

 

3)         Objective 3 is accomplished through the problem sets, course project, and exams.  Each student has the opportunity to use the accompanying statistical package or statistical calculator to conduct statistical analyses. 

 4)         Objective 4 is accomplished through the course project and exams.  For the course project and the exams, the students must decide which statistical procedure best addresses the research questions and be able to summarize the findings in a clear and succinct way.

 5)         The exams, problem sets, current event, and course project are designed to assist the student to bring all aspects of the course together so that the student not only has a working knowledge of statistical concepts and procedures, but also how statistics are applied and used outside of the classroom.  Portions of the class discussion focus on how statistics can be used in the student’s everyday personal and work lives. 

 Review of Basic, Broad Statistics Concepts (4%).  Students learn/review basic statistics concepts such as the distinction between descriptive and inferential statistics, as well as the distinction between a population and a sample.

Sampling Techniques and Common Sampling Errors (4%). Students will also learn about proper sampling methods, as well as common errors that occur during the sampling process that can lead to poor data collection.

Descriptive Statistics (12%). Students learn/review basic descriptive statistics such as the mean, median, mode, variance, standard deviation, coefficient of variation, skewness, and coefficient of correlation. 

Expected Wealth Hypothesis and Discrete Random Variables (12%). Students learn how to determine expected wealth in an uncertain business climate.  Students also learn how to quantitatively assess risk by using such metrics as standard deviation and the coefficient of variation.  Also, students will learn about binomial distributions, Poisson distributions, and various counting rules.

Normal Distribution (9%).

Sampling Distributions (9%).  Student will become familiar with the properties of a normal distribution, how to use Z tables when working with both numerical and categorical data, and how to apply the concepts of the normal distribution to that of sampling distributions.

Confidence Interval Estimation (8%). Students learn how to construct confidence intervals for both numerical and categorical data, and then learn how this concept can be applied to a real-world business scenario.

 Hypothesis Testing (10%).  Students learn how to use apply hypothesis testing to both numerical or categorical data sets to assess the validity of statements made in a business setting.  This includes introduction to such things as: the null and alternative hypotheses, critical and observed values of test statistics, fail to reject and rejection regions, and both one and two tailed testing.

 Simple Linear Regression (8%).

Multiple Linear Regression (12%).Students learn simple and multiple regression analysis, and then learn how to use regression results in a real-world setting.  Most important is for students to know how to interpret regression results (coefficients, t-scores, p-values).  Students should be shown how to work with dummy variables and how to test for non-linearity. Students should also be introduced to common problems such as multicollinearity, autocorrelation, and heteroskedasticity.  Time permitting, students learn how to use Excel to actually generate regression results from scratch with a raw data set.

 Forecasting (12%).Students become familiar with the trend, seasonal, and cyclical components of a data series, and how to separate these components from one another.  Students should be shown various smoothing techniques such as moving averages and exponential smoothing.  Students should also be introduced to various methods of modeling trends (e.g. linear, quadratic, exponential).

 

Siegel, Andrew F. (2003).  Practical Business Statistics, Fifth Edition. Irwin/McGraw Hill Publishing Co., (ISBN 0-07-249905-2).

Students are expected to visit the class web site before the first night of class. 

http://mysite.verizon.net/busn5760

All course materials, documents, and test will be posted on the course web site through out the semester.  Final grades will NOT be posted on the web site.

Students will locate a current newspaper or magazine article that deals with a statistical issue. 

1. Each student in the class will present one current event article to the class during the semester. Presentation should be no longer than 10 minutes.

2. At the beginning of each class, students will discuss the current event articles they have found in magazines, newspapers, the internet, etc. with the class. 

3. A summary of the article, not to exceed two double spaced pages, will be prepared and submitted to the instructor.  The summary should include a brief synopsis of the article, how the article relates to a statistical issue, and the source of the article.

Students are expected to spend sufficient time outside of class to prepare for each class session, as well as studying for the examinations, and doing the problem sets for each chapter.  This effort will normally exceed eleven hours for each class session.