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CAIS 102 — Business Statistics I School of Business — Fall 2013 Instructor: Timothy Dorr, DM Office: Man 217B Hours: As shown & by appt Email: [email protected] Time 9:30-10:45 11:00-1:00 Monday Prerequisites: CAIS 101 Class Meetings: As shown Room: Computer Lab Home Phone: 858-1619 (be reasonable) Tuesday Office 1:30-2:45 CAIS 102 Wednesday Thursday Office Office Office Office CAIS 102 3:00-4:15 Office Office Office 4:30-5:45 Office CAIS 101 CAIS 101 Alt. Fridays Office Open Computer Lab Open Computer Lab Final Exam Schedule: Week of Dec 9 – Dec 13, 2013 Course Date Time CAIS 101 CAIS 102 Note: Final Exam schedule is unavailable at the time of publication. Course Content and Description: Today businesses are awash in data, and what businesses will pay for is an ability to make sense out of terabytes (a thousand gigabytes) of data. Business Statistics is a way to summarize data and to infer characteristics of such large populations of data. It is not mathematics. It is one of the most widely applicable tools available to business people, and also one that is not widely mastered. Knowledge of statistics and data management will make you an exception and thus more employable. This is the second of two undergraduate courses in the use of statistics in business. Again, this is not a math course. This is a course about how to use data for making more rigorous business decisions. We begin with a review of descriptive statistics, discrete probability distributions, and the normal distribution which were covered in CAIS 101. For the remainder of the semester we will examine the application of statistics through sampling, confidence interval estimation, hypothesis testing, and nonparametric statistics. As in CAIS 101we will continue to use Excel for the work in this course. Additionally we will examine other proprietary statistics applications. Topics: 1. Review of descriptive statistics, discrete distributions, and the normal distribution. 2. Introduction to Probability a) Definition and applications b) Random Variables: discrete and continuous distribution 3. Sampling and the Central Limit Theorem a) Sampling techniques b) Application of the Central Limit Theorem ASSESSMENT 1 4. Statistical estimation and Confidence Intervals a) Measuring the relationship between statistics (samples) and parameters (populations). b) Validating the strength of an estimate ASSESSMENT 2 5. Hypothesis Design and Testing a) Defining a hypothesis: what to test b) Null versus alternative Hypotheses c) Hypothesis tests of the mean using interval data d) Hypothesis tests of the mean using ordinal data ASSESSMENT 3 6. Two-sample Hypothesis Testing a) Evaluating statistically significant differences among samples b) Statistics selection based on sample size variations c) Statistics application d) Sample mean variation validity: p-values e) Testing proportion data ASSESSMENT 4 7. Introduction to Inferential Statistics a) Analysis of Variance (ANOVA) b) Correlation and Linear Regression 8. FINAL EXAM Expected Outcomes: At the end of this course a successful student will be equipped to discuss the application of appropriate statistical tests which use sample measurements for mean and variance as ‘best’ estimators for a population that exhibits normal data distribution characteristics. Within a business setting this student will be ready to discuss various tactical marketing research projects and proposals and to make informed decisions regarding their respective value to an organization. The student will be prepared to take additional graduate level courses in business quantitative analysis. Text and Recommended Reading: The official text for the course: Statistical Techniques in Business & Economics, 12th ed., Lind, Marchal, and Wathen, New York, NY: McGraw-Hill, Irwin. I will loosely follow the chapters in the text and you must buy a textbook. To stay with the material being covered you are encouraged to have the text within three weeks of the start of class. If this becomes an issue let me know. The text serves as an ancillary learning tool and resource. In a real business situation if you have a problem you look up the appropriate principles in a reputable resource and apply those principles to your specific problem. That said, we will be doing some problems from the text. Such problems are contrived to illustrate a specific principle or application. I encourage students of modest financial means to find a used copy of the text online rather than pay full price at the bookstore. Introductory Statistics have not changed much in the last fifty years and previous editions of the text from a few years ago are entirely acceptable. If you choose to use an edition from more than five years ago, you may find that the software references are somewhat dated, even though the subject material is current. Grading Application and Ranges: Grades are based on performance not on effort, desire, or need. English skills, written and spoken, are a part of every student's grade on every assignment. If you need a particular grade, to maintain your scholarship status, your athletic eligibility, or any other reason, the time to start working toward fulfilling that need is now. In-term assessments: 40% Class participation: 20% Final Exam: 40% Failure to earn a score of 50% or greater on the final will result in a course failure. Grade Percentage A AB+ B BC+ C CD+ D DF 95+ 90-94 87-89 84-86 80-83 77-79 74-76 70-73 67-69 64-66 60-63 <60 At the end of the course you will have a raw course score available through the Canvas® gradebook. This grade may be adjusted to reflect the application of a normal distribution in keeping with statistical analysis prior to your grade being submitted to the registrar.