Fall 2011 Course Outline BSTAT 3321 Business by linzhengnd

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									                     Course Outline BSTAT 3321: Business Statistics I
                                                            Fall 2011

          Professor    Mary M. Whiteside, Ph.D.
            Section    004                          ID   22560
       Prerequisites   INSY2303 and Math1315 (or business calculus) plus use of a spreadsheet
      Hours & Room     Tuesday, Thursday 5:30 - 6:50                COBA 147
               GTA     Taeuk Kang          Taeuk.Kang@mavs.uta.edu
               Text    Statistics for Managers, custom edition for UTA by Levine and others, Pearson
                   only if you are not required to take BSTAT 3322; otherwise full 6th edition.
         Software Excel
     Office Hours T 4:00 - 5:00, Th 1:00 - 2:00 and by appointment Room B513
 GTA Office Hours Tuesday and Thursday 7 - 9 pm                    B508
           Phone (817) 272-3517
              FAX (817) 272-5801
            e-mail whiteside@uta.edu
        WebPage http://wweb.uta.edu/insyopma//whiteside/
        Class List The name of our list is BS1. To subscribe send an email after August 25 to
                                              Subject and message are 'Subscribe bs1 <name>'
                       listserv@listserv.uta.edu
      Grading Policy Class exercises & homework (10/12+)                 20%
                   Exams (3)                                             30%
                   Project                                               20%
                   Final Exam                                            30%
                                                                       100%
          Homework assignments are due at the beginning of class and will not be accepted late.
          Various extra credit opportunities for the homework portion of your grade are available on the web.
          Class exercises are unannounced. There will be no make-up exercises or exams. If you must
          miss an exam for any reason, please notify me at the first opportunity. At my discretion you
          may be allowed to count the Final Exam as 40% of your grade to replace the missed exam.


Week        T Date     Topics (Tuesday/Thursdau)                                Text      Homework: due Thursday

  1         23-Aug     Pre sem/Introduction
  2         30-Aug     Graphs with Excel/Numerical Descriptive               Chapter 1-2                 1
  3         6-Sep      Lab Study/Numerical Descriptive                       Chapter 3                   2
  4         13-Sep     Numerical Descriptive/Probability                     Chapter 4                   3
  5         20-Sep     Review/Thursday, Exam 1 Chs. 1-3
  6         27-Sep     Probability/Binomial Distribution                     Chapter 5                    4
  7          4-Oct     Normal Distribution/Sampling Distributions            Chapter 6                    5
  8         11-Oct     Sampling Dist/Th., Exam 2 on Ch. 4-7                  Chapter 7                    6
  9         18-Oct     Estimation                                            Chapter 8                    7
 10         25-Oct     Hypothesis Testing                                    Chapter 9                    8
 11         1-Nov      Hypothesis Testing                                                                 9
 12         8-Nov      Review/Thursday, Exam 3 Ch. 8-9                                                   10
 13         15-Nov     Regression                                            Chapter 13                  11
 14         22-Nov     Regression/Thanksgiving                               Chapter 13
 15         29-Nov     Regression                                            Chapter 13                  12
     16        6-Dec    Regression/Review                            Chapter 13          Projects Due
     17        13-Dec   Tuesday Final Exam 5:30 - 8:00 Ch. 1-9,13    Chapter 1-9,13

Course objective:       To enable the students to find and solve problems in business and economics
                        using selected statistical methods. See attached learning outcomes.

If you require an accommodation based on disability, I would like to speak with you
 during the first week of the semester, to appropriately accommodate you.
Vision statement for BSTAT3321

they will encounter in their is that students will become Students will be able to of statistical
Our vision for STAT3321 professional and personal lives.competent consumers perform basicinformation
statistical
analyses and to think critically when interpreting statistical results.

Learning outcomes for BSTAT3321

1. The student will be able to *evaluate verbal, numeric, and graphic descriptions of a data set.
2. The student will be able to select a simple random sample and to evaluate the role of randomness in
data collection (both sampling and experimentation). The student will restrict causal inferences to data
collected from experiments.
3. The student will be able to analyze probability problems by choosing and applying basic laws of
probability, computing and interpreting results.
4. The student will be able to distinguish between discrete and continuous random variables, find
binomial and normal probabilities using tables, and compute expected value and variance for a binomial
distribution. The student will be able to analyze binomial and normal probabilities.
5. The student will be able to analyze scenarios appropriate for the Central Limit Theorem and choose
6. The student will be able to set up, interpret and interpret confidence intervals for sample proportion.
the sampling distributions to find and calculate,probabilities for the sample mean and a population mean
and a population proportion and to determine sample sizes for given levels of confidence and margins
of error.
7. The student will be able to set up and test hypotheses about a population mean and a population
proportion and to interpret the results.
                                use a interpret simple linear regression models along with the usual
8. The student will be able to fit andsoftware package in order to perform appropriate statistical
9.
analyses.
10. The student will be able to select and justify appropriate statistical techniques for a given scenario.

 *For all topics, the student will be able to demonstrate knowledge and comprehension, for example by
defining the new terms in the topic and describing and restating the concepts covered in each topic.
The abilities to
apply, analyze, synthesize and evaluate are assumed to be hierarchal. In other words, the ability to
evaluate and synthesize presumes an ability to analyze and apply. Likewise the ability to analyze
presumes an ability to apply.

The course grade reflects the proportion of topics that the student masters.
cal information

								
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