Introduction to Statistical Methods in Economics

Lecture Notes

SES #	TOPICS
Probability distributions and random variables
I. Probability
1	Sets and events (PDF)
2	Probabilities and counting rules (PDF)
3	Conditional probability and independence (PDF)
II. Random variables and distribution functions
4	Bayes theorem and random variables (PDF)
5	Discrete and continuous random variables (PDF)
6	Probability distribution functions (PDFs), cumulative distribution functions (CDFs), joint distribution of 2 or more random variables (PDF)
7	Joint and marginal distributions (PDF)
8	Review (PDF)
Expectations and transformations of random variables
III. Transformations of random variables
9	Functions of random variables (PDF)
10	Functions of several random variables (PDF 1) (PDF 2)
IV. Expectations and conditional distributions
11	Order statistics and expectations (PDF)
12	Median, quantiles, and variance (PDF)
13	Covariance and conditional expectations (PDF)
V. Special distributions
14	Conditional expectations and special distributions (PDF)
VI. Law of large numbers and central limit theorems
15	Law of large numbers (PDF)
16	Review (PDF)
Estimation and hypothesis tests
VII. Estimation methods and properties
17	Central limit theorem, estimators, bias, and consistency (PDF)
18	Constructing estimators (PDF)
VIII. Confidence intervals
19	Confidence intervals (PDF)
20	Confidence intervals (cont.) (PDF)
IX. Hypothesis testing
21	Hypothesis tests (PDF)
22	Hypothesis tests (cont.) (PDF)
23	Hypothesis tests (cont.) (PDF)
24	Review (PDF)