Statistical Methods for Managers
This course will provide an introduction to the principles of data collection, description and analysis. You will learn the basic tools of statistical inference and modeling, as well as some fundamentals of designing a statistical study, how to sample and collect data, and which statistical techniques are appropriate. You will also learn how to interpret statistical output, and how not to be fooled by statistical studies.
At the end of this course, you should be able to - Use Minitab and Excel to create graphs of sample data - Summarize a set of observations by reporting a measure of center and dispersion - Use Bayes' Rule to incorporate information and revise probabilities - Find and interpret the probability for a random variable which has a normal distribution - Explain what sampling error is and why it exists - Classify data by type and use the proper summary statistics and tests for the data type - Use sample data to estimate descriptive measures of populations when census data is unavailable, and give a measure of the accuracy and precision of the estimate - Interpret the p-value, test statistic and other Minitab and/or Excel output from a test of hypotheses, confidence interval, and linear regression - Explain what it means if test results or poll differences are statistically significant - Apply the concepts of sampling, estimation, and hypothesis testing to real world examples from polls and surveys, clinical trials and observational studies