2. Download and install R and R Studio. a. Download and install R FIRST! ii. Download R from R- Site and install R: project.

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1 First Assignment 1. Read chapters 1-3 of your textbook 2. Download and install R and R Studio a. Download and install R FIRST! i. Watch the how to video: ejtnbddkgjgjzaqcy6oxmsxahu ii. Download R from R- Site and install R: project.org/ iii. Download and install R- Studio: 3. Watch R videos to get up to speed a. Getting Started with R: ejtnbddkgjgjzaqcy6oxmsxahu&index=2 b. Import Data, Copy Data from Excel to R, Both.csv and.txt Formats: ol9- ejtnbddkgjgjzaqcy6oxmsxahu 4. Download factbook.xlxs from Files area of Canvas for this course and convert it to a comma- delimited file (*.csv) 5. Load and attach the comma delimited file into R Studio 9- ejtnbddkgjgjzaqcy6oxmsxahu 6. Create a boxplot for the variable Exports 7. Calculate summary statistics for the variables Exports and Imports 8. Print the results and turn them in

2 Instructor: Jon Weimer, Ph.D. Wednesdays 6:00 PM 9:20 PM Telephone: (816) mobile Credit Hours: 3 E- mail: jweimer62@gmail.com Pre Req: MA 115 or Equiv I do not have a campus office but will be available before and after class in the course classroom to discuss any questions that you may have. I encourage you to use e- mail to raise questions. Text: Anderson, David R., Sweeney, Dennis J., and Williams, Thomas A. (2011) Statistics for Business and Economics. Eleventh Edition, Southwestern, ISBN: (Always bring your copy of the text and a calculator to class) Course description: Introduction to basic statistical techniques for students in business and economics. Statistics is the study and application of how data are collected, analyzed, presented and interpreted. A major reason for collecting, analyzing, presenting, and interpreting data is to provide the information needed to make good decisions. The proper design of statistical studies, descriptive statistics, statistical inference, and examining the relationship between two or more variables is emphasized. Assessment: Student grades will be based on exams and labs. Teaching method: Classes will consist of lectures, class discussion, classroom activities, and hands- on computer work. Assessment of Intended Learning Outcomes: MBA Outcomes Formulate and solve problems through systematic analysis (Assessment: problem questions on exams)

3 COURSE REQUIRMENTS: READING: Students are expected to read the assigned chapters before class. I also recommend you work through the solved problems until you have mastered the topic. Focus on problems you don t already know how to solve. EXAMS: There are 2 exams. Exams assess your mastery of material covered in class, assigned chapters from the textbook, and any assigned supplemental readings. The exams are case- based problems of the kind you d experience in the real- world. The exams are non- cumulative and focus on the units that we ve completed; however, the subject matter, by its nature, IS cumulative (i.e., later topics build on the mastery of earlier material). LABS: Labs are something unique to my classes. A lab is like a quiz, but... since most work is now done by teams, you solve a problem as a team. A Note on Homework: Homework is not assigned or graded. Homework is practice of the skills you re learning (like learning the piano). Without practice, you simply will not succeed. There is no graded homework in the real world. You are given a task by management and expected to complete it successfully. Thus, my expectation is that you will do the solved exercises until you have mastered a particular topic. Learning occurs, not by getting problems right, but by getting problems wrong and doing a post- mortem on them to see where you made mistakes. A Note on Extra Credit: There are no do- overs in the real world. Work is expected to be completed on time and accurately. In the real world, if you miss deadlines or fail in the completion of a task, at best you will get reprimanded, and at worst you ll get fired. So... no extra credit. This class is just like a job. Do it right the first time. If you have questions on completing a task or need clarification, ask the manager (me). ABSENCES: Many students struggle with this material. As a graduate student, my expectations are that you take ownership of your own performance and success. Student absences are strongly discouraged. Absences for exams must have been approved prior to the time of the exam and permission is given only in the direst of circumstances (e.g., illness, car accident, death in the family, business trip, etc.; a vacation is not a sufficient excuse, so plan your travel accordingly). If your absence has not been approved prior to the exam you will receive a zero for that test. There will be no make- ups for the final exam.

4 COURSE EVALUATION: The following indicate the weights given to the various components of the course. Examinations points each 80 points possible Labs points each 20 points possible 100 points possible Your final grade will be determined as follows: A: 90% or above B: 80 to - 89% C: 70 to - 79% D: 60 to - 69% F: Below 60% TENTATIVE COURSE SCHEDULE: Date Topic Chapter Exam/Lab 01/06/16 Describing data with tables and graphs 2-3 Describing data with numbers R vs. Excel 01/13/16 Introduction to probability 4-5 Lab 1 Discrete probability distributions 01/20/16 Continuous probability distributions 6-7 Sampling and sampling distributions 01/27/16 Interval estimate 8-9 Lab 2 Hypothesis testing 02/3/16 Inference about means and proportions Midterm Exam Hypothesis testing 02/10/16 Tests of goodness of fit and independence Lab 3 Experimental design and ANOVA 02/17/16 Simple linear regression Multiple regression 02/24/16 Regression Analysis: Model building 16 Lab 4 Logit regression 03/2/16 Non- parametric methods Statistical quality control 03/9/16 Index Numbers Time Series Analysis Lab 5 03/16/16 Final Exam

5 OTHER POLICIES: 1. Attendance: Avila University requires regular attendance. Absences beyond two will result in point penalties, unless otherwise negotiated with me. This negotiation will occur prior to the missed class. It is your responsibility to obtain class notes from one of your classmates and obtain any handouts missed. Furthermore, you will be responsible for being aware of all announcements made in the missed class. 2. Active class participation is strongly encouraged. 3. Cheating and plagiarism: The policy of Avila University concerning cheating and plagiarism will be strictly followed in this class. The University s policies concerning academic honesty can be found in the Academic Policies section of the University catalog. 4. Students with disabilities: Please discuss your situations with me so that suitable accommodations can be arranged.