Business Statistics I |
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This web-based course is the first in a two-course series designed to introduce working professionals and students to the concepts of basic statistics as applied to business and economics. The course is intended for those with little or no background in statistical analysis or advanced mathematics. Taught from an applied perspective, the course utilizes the data analysis tools available in Microsoft Excel as well as powerful statistical packages widely used in both industry and academics. Upon completion of the two-course series, the student will have acquired the skills to conduct statistical analyses valuable not only in business and economics, but necessary for other social and physical sciences as well.
Course Specifications: |
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Length: |
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8 weeks |
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Weekly time commitment: |
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Approximately 5 to 10 hours |
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Prerequisites: |
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Basic knowledge of Microsoft Excel is recommended. |
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Tuition: |
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US $1,195 |
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Additional expenses: |
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Textbook and statistical software package |
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Course Materials - Text and Software
The course is based upon the text, Statistical Techniques in Business & Economics, by Douglas A. Lind, William G. Marchal, and Samuel A. Wathen. Published by McGraw-Hill Higher Education, the text is in its 14th Edition. MegaStat for Excel is a sophisticated and user-friendly statistical package which accompanies the text.
The text can be purchased from www.amazon.com
System Requirements
The minimum system requirements necessary to complete the course are as follows:
- A PC-based computer
- RAM: 1GM or more
- Processor: 1GHz 32-bit or 64-bit
- Hard disk spack: 200MB minimum
- Operating System: Microsoft Windows 2000, XP, Vista or Windows 7
- Access to the internet and an email account with the ability to send and receive large Microsoft Excel and Word files
- Adobe Reader: Version 5.0 or higher
Course Format
The course runs 8 weeks. Each week the student will complete the assigned readings in the text and review the associated lecture notes and Powerpoints. End-of-chapter exercises and case studies apply the concepts and computational tools to the material introduced in the text. A weekly Personal Assessment will enable the student to test his or her knowledge of the chapter material. Students will also have the opportunity to apply the statistical analysis techniques they have learned to a real world situation of personal or professional interest.
Course Content
Unit 1: Describing Data: Frequency Distributions and Graphic Presentation
The first unit introduces the student to various types of statistics and levels of measurement. Students learn how to construct frequency distributions. Various methods of graphically presenting data are explored. The computational tools used in this course are introduced and include: Microsoft Excel and MegaStat.
Unit 2: Describing Data: Numerical Measures and Data Exploration
This unit discusses numerical ways of describing data including measures of location and dispersion. New methods of displaying and exploring data are introduced. Data interpretation is a primary concern. Data analysis tools are demonstrated.
Unit 3: Probability Concepts
Unit three discusses probability and various approaches to assigning probabilities. Rules for computing probabilities are outlined. Bayes� Theorem is introduced. Discrete probability distributions are explained in detail. Additional computational tools and software commands are demonstrated.
Unit 4: Continuous Probability Distributions, Sampling Methods, and the Central Limit Theorem
This unit introduces the standard normal distribution and its applications. Sampling methods are outlined and The Central Limit Theorem is discussed in detail. More software commands are introduced.
Unit 5: Estimation, Confidence Intervals, and Hypothesis Testing
Unit five covers the use of point estimates and confidence intervals. A Five-step procedure for hypothesis testing is outlined in detail. One-tailed and two-tailed tests of significance are demonstrated. Additional techniques of data analysis are demonstrated using the software.
Unit 6: Two-Sample Tests of Hypothesis and Analysis of Variance
This unit introduces two-sample tests of hypotheses using independent and dependent samples. Concepts involving two-sample tests about proportions and comparing population means with small samples are provided. Techniques for comparing dependent and independent samples are discussed. The F Distribution and ANOVA test are detailed. Two population variances are compared. Two-way analysis of variance is introduced.
Unit 7: Linear Regression and Correlation
Unit 7 introduces correlation and linear regression. The coefficient of correlation and correlation of determination are defined. Regression analysis is introduced including the Least Squares Principle. The assumptions underlying linear regression are detailed. Confidence and prediction intervals and testing of significance are discussed. Linear regression is illustrated.
Unit 8: Putting It All Together
This unit reviews the statistical concepts introduced and provides an additional opportunity to apply the data analysis techniques acquired to a variety of problems encountered in the business world. Students may also use this final week of the course to study a situation of personal or professional interest.
Comments or Questions?
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