Assignment
Introduction
The significant advances in computing and communication technologies over the past two decades have resulted in a business environment today that increasingly requires managers who can use the principles of statistical analysis to make effective decisions. Managers with these capabilities will be able to 1) consider richer sets of alternatives, 2) more deeply understand and question assumptions, and 3) consider more diverse measures of performance. This course will improve a student's capabilities in each of these areas.
Catalog Course Description
This course covers the basic techniques of applied statistical analysis beginning with an exploration of the meaning of data. Methods of describing data on individual variables and relationships between variables are covered. Sampling and probability are introduced as a basis for understanding how to infer results from samples to the populations from which they are drawn. These techniques include estimation, tests of mean differences, differences in distributions, and regression.
Student Learning
Summary: This course is designed to introduce students to the practice of introductory statistical analysis. Coverage will include examining data distributions, examining relationships between variables, probability theory including standard probability distributions such as normal and binomial; sampling distributions, the basic statistical inference methods, and applied linear regression techniques/forecasting. This course will emphasize statistical thinking. While the foundations of statistical analysis are rooted in math theory, the practice of statistics today involves learning a process of scientific inquiry. Statistics is the science of data. In this course, students will work hands-on with real data and develop questions they seek to answer with appropriate data analysis.
Learning Outcomes
Goal 1: Given a description and demonstration of statistical concepts, techniques, and calculations, students will be able to perform and interpret statistical analyses within the scope of topics listed in the Course Plan.
Goal 2: Given demonstrations of the use of Microsoft Excel tools for statistical analysis, students will be able to match appropriate tools to types of data and analysis goals, and to perform the targeted analysis with the Excel tool.
Goal 3: Given a survey of statistical techniques outlined in the course plan, students will be able to name and explain all techniques, including matching appropriate techniques to specified analysis goals.
Goal 4: Given a description and examples of basic principles of experimental design, including the production of data, analysis and findings, students will be able to: 1. Define key terms and concepts associated with experimental design, 2. Recognize various designs when given in a case problem, and 3. Determine appropriate statistical analysis to use within the experiment.
Goal 5: Given examples of statistical reporting, students will be able to generate appropriate statistical reports, including description of the research problem, formulation of research questions, selection of statistical methods, analysis of data/testing, and a summary of key findings.