This document provides the syllabus for the Business Statistics 41000 course. It outlines the course details, including the focus on applying quantitative and data analytic tools to business decisions. Topics covered include descriptive statistics, probability, statistical modeling and inference, linear regression, and time series analysis. Students will be evaluated based on homework assignments, a midterm exam, and a take-home project. The syllabus instructs students on resources like the course website, textbook, and software for completing assignments.
This document provides the syllabus for the Business Statistics 41000 course. It outlines the course details, including the focus on applying quantitative and data analytic tools to business decisions. Topics covered include descriptive statistics, probability, statistical modeling and inference, linear regression, and time series analysis. Students will be evaluated based on homework assignments, a midterm exam, and a take-home project. The syllabus instructs students on resources like the course website, textbook, and software for completing assignments.
This document provides the syllabus for the Business Statistics 41000 course. It outlines the course details, including the focus on applying quantitative and data analytic tools to business decisions. Topics covered include descriptive statistics, probability, statistical modeling and inference, linear regression, and time series analysis. Students will be evaluated based on homework assignments, a midterm exam, and a take-home project. The syllabus instructs students on resources like the course website, textbook, and software for completing assignments.
This document provides the syllabus for the Business Statistics 41000 course. It outlines the course details, including the focus on applying quantitative and data analytic tools to business decisions. Topics covered include descriptive statistics, probability, statistical modeling and inference, linear regression, and time series analysis. Students will be evaluated based on homework assignments, a midterm exam, and a take-home project. The syllabus instructs students on resources like the course website, textbook, and software for completing assignments.
Ofce 441: I will be available Tuesday afternoon by appointment (email is best) TA: Laslo Korsos lkorsos@chicagobooth.edu Course Information This course focuses on the application of data analytic, quantitative tools in business decisions. We will start with a quick review of basic data analytic tools, followed by probability tools and concepts and statistical decision making tools. Students will learn how to use Statistics to analyze a variety of complex real world problems. Numerous empirical examples from economics, nance, marketing, politics and sports, etc are used to illustrate the material covered. Emphasis will be placed on understanding concepts and analysis of data. The topics covered are: (i) descriptive statistics and plots used to summarize data; (ii) random variables and expectation; (iii) modeling and inference: population and sample quantities, condence intervals, hypothesis tests and p-values; (iv) linear regression; (v) introduction to multiple regression; (vi) basic times series: autocorrelation, autoregres- sion, the random walk. Lecture Notes The lecture notes for the course are provided directly on the course website. There is no course packet. Datasets etc and previous midterm exams are also provided on the course website. They provide useful information as to the level of the course. I recommend Statistical Techniques in Business and Economics by Lind, Marchal and Wathen. This classic Business Statistics book is now in its 14th edition. If you have the 13th edition that will sufce. Although some of the latter chapters of this text are advanced, most of the material is covered by the course. Evaluation Grades will be determined by homework assignments (20%), a midtermexam (40%) and a take-home project (40%). 1 Preliminary, Subject to Change Posted: 07.13.11 There are weekly homework assignments collected each week. Students are encouraged to form groups (of at most three) for homework but to write-up individual assign- ments. Homework assignments should be submitted in class and should have a clear and professional presentation. Late homework assignments will not be accepted. Home- works will be graded on a check plus, check, check minus basis. The take-home project is an individual project to be discussed only with me. Computing You can choose which software you use. I recommend learning R as it is used in further Stats course at Booth. This open-source software is available for free download at www.r-project.org and you can nd doumentation there. Alternatives are Ex- cel/Minitab. For more information on a student version of Minitab see www.minitab.com. I will demonstrate data analysis in class. The website contains code in code.R for the notes. You may use either software for your project. Prerequisites There are no prerequisites for the course. For a rst class assignment reading the chapters 1-4 of the textbook will give you a good idea of the level of the class. Students must adhere to our Booth Honor Code standards I pledge my honor that I have not violated the Honor Code during this examination or assignment. Schedule See course website. 2 Preliminary, Subject to Change Posted: 07.13.11