SEDS 531
Introduction to Statistical Data Processing
Organization and application of computers and statistical techniques to data processing. Data handling in terms of coding, preparation, acquisition (with and without computers), screening and reduction; summarization, tabulation and analysis; random variables, statistical estimation and hypothesis testing, enumerated data analysis, linear models (regression, correlation, analysis of variance).
Course Objectives:
This course will help students acquire the fundamental skills that will enable them to learn and understand the complicated statistical analysis that can be directly applied to different types of data, encountered in real-life situations.
Recommended or Required Reading:
Steel, R.G.D. and Torrie, J.H. (1960) Principles and Procedures of Statistics. Mc. Graw Hill ,Milton, J.S. and Arnold, J. C. (2003). Introduction to Probability and Statistics. 4th Ed. New York: McGraw-Hill. ,Allen B. Downey, Think Stats: Probability and Statistics for Programmers. 2e
Course Outcomes:
1. To be able to summarize experimental data
2. To be able to understand probability, random variables and probability distributions
3. To be able to apply estimation of parameters, to understand concept and philosophy of testing scientific hypotheses
4. To be able to understand experimentation concept and to be able to design and analyze experiments
| Week | Topics |
|---|---|
| 1 | Data; Classification, Summarization and Tabulation of Data; Descriptive Statistics and Coding |
| 2 | Introduction to Probability |
| 3 | Conditional Probability, Random Variables, Expected Values |
| 4 | Discrete Distributions, Binomial, Negative Binomial and Poisson Distributions |
| 5 | Continuous uniform, Normal, Gamma, Exponential and Weibull Distributions |
| 6 | Midterm |
| 7 | Introduction to Statistical Inference, Point Estimation, Interval Estimation |
| 8 | Tests of Hypotheses, Large Sample Tests |
| 9 | Tests of Hypotheses, Single Sample Tests, Two Sample Tests |
| 10 | Tests of Hypotheses, Small Sample Tests |
| 11 | Analysis of Categorical Data (Chi-Square Tests) |
| 12 | Simple Linear Regression and Correlation |
| 13 | Introduction to Multiple Linear Regression |
| 14 | Introduction to Experimentation, Analysis of Variance |
Grading:
Midterm: 30%
Homework: 10%
Research Presentation: 30%
Final: 30%