Statistical Inference
A basic estimation including unbiased, maximum likelihood and moment estimation; testing hypotheses for standard distributions and contingency tables; confidence intervals and regions; introduction to nonparametric tests and linear regression.
STAT51700
Credit Hours:
3Learning Objective:
Understanding the basic statistical inference methods.Description:
A basic estimation including unbiased, maximum likelihood and moment estimation; testing hypotheses for standard distributions and contingency tables; confidence intervals and regions; introduction to nonparametric tests and linear regression.
Topics Covered:
1. Sampling distributions; 2. Point Estimation; 3. Confidence interval; 4. Hypothesis Testing; 5. Linear RegressionPrerequisites:
This course emphasizes the statistical theory. The students need to have the background on calculus and probability. The prerequisite for this course is STAT 516.Applied / Theory:
35 / 65Homework:
10 homeworks. Will be accepted via email at wangxiao@purdue.edu.Projects:
None.Exams:
1 midterm exam and 1 final exam.Textbooks:
Official textbook information is now listed in the Schedule of Classes. NOTE: Textbook information is subject to be changed at any time at the discretion of the faculty member. If you have questions or concerns please contact the academic department.REQUIRED - Introduction to Mathematical Statistics (7th Edition) by Robert V. Hogg (Author), Joeseph McKean (Author), Allen T Craig (Author) - ISBN: 0321795431.