Course Description
Random sampling and the sampling distributions: t, chi-square and F ,Point Estimation ,Properties of estimators, unbiased, consistency and efficiency, lower bound of the variance of unbiased estimators , Methods of estimation: maximum likelihood, moments, least squares , Interval estimation, pivotal quantity ,Testing hypotheses, The Bayesian Approach
Course Objectives & Outcomes
The objectives of this course are:
- Apply basic statistical concepts that are commonly used in science.
- Studying the theoretical bases for the statistical inference methods to have a good knowledge of key statistical concepts such as probability distributions, estimation and hypothesis testing .
Upon successful completion of this course, the student will be able to:
- Define the properties of estimators
- Identify the procedures of estimations
- Identify the Bayesian Approach
- Describe the steps of testing hypothesis
- Compare between the methods of estimation and differentiates between them.
- Explain the outputs of estimations which it is produced from the statistical package
- Explain the pivotal quantity
- Solve several applications for the statistical estimations and testing hypothesis
References
1. Wackerly,D. Mendenhall.W&Scheaffer,R.(2008),Mathematical statistics with applications, Thomson Learning, ISBN-13: 978-0-495-38508-0.
2. Devore, J. &Berk, K.(2007), Modern Mathematical Statistics with Applications , Thomson,ISBN : 0-534-40473-1 .
3. Casella, G. and Berger, R. (2001),Statistical Inference. 2nd Edition, Brooks/Cole .ISBN-13: 978-0534243128 ,ISBN-10: 0534243126.
Course ID: STAT 404
| Credit hours | Theory | Practical | Laboratory | Lecture | Studio | Contact hours | Pre-requisite | 3 | 2 | 2 | 4 | STAT 306 |
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