Course Introduction:
In Introduction to Applied Statistics, you learn to apply statistical methods and technological tools such as spreadsheets to solve real problems using data. With an emphasis on statistical reasoning and data analysis, this course introduces the science of collecting, organizing, and interpreting numerical data. Understand key concepts including study design, descriptive statistics, probability theory, and statistical inference, and learn when to use one or two sample t-tests, one- or two-proportion tests, correlational methods, regression analysis, and analysis of variance.
Course Objectives:
The objective of this course is to provide an understanding for the graduate business student on statistical
concepts to include measurements of location and dispersion, probability, probability distributions, sampling,
estimation, hypothesis testing, regression, and correlation analysis, multiple regression and business/economic
forecasting.
Learning Outcomes:
Upon completion of this course, the student will have reliably demonstrated the ability to:
- Use the basic probability rules, including additive and multiplication laws, using the terms, independent and mutually exclusive events.
- Compare random variables and probability including discrete and continuous random variables, expectation and odds, the poisson distribution.
- Use the binomial probability distribution, including requirements, distribution, mean and variance, and making decisions.
- Use the normal probability distribution including standard normal curve calculations of appropriate areas, sampling distributions of statistics, central limit theorem, sampling distribution of sample mean, normal approximation to the binomial distribution, and statistics that passes normal sampling distributions.
- Test large estimation principles including confidence intervals and point estimates for estimating a population mean, estimating the parameter of a binomial distribution, estimating the difference between two means, estimating the difference between two binomial parameters, and choosing the sample size.
- Examine large sample tests of hypothesis including elements of a hypothesis test, type I and II errors, and using p values to indicate significance tests for population proportion and difference between two population proportions.
Course Assessment Strategy:
Class attendance: 07%
Quiz: 15%
Assignment: 05%
Presentation: 08%
Mid-term: 25%
Final: 40%
Total 100%