1. Estimation

1.1 Introduction

1.2 Point estimation

1.3 Properties of point estimators

1.4 Interval estimation

2. Hypothesis testing

2.1 Introduction

2.2 Most powerful test. Neyman-Pearson Lemma

2.3 Testing of simple vs composite hypotheses

2.4 P-value

2.5 Normal populations - mean and variance testing

2.6 Normal populations - Testing equality of two populations  

2.7 Non-normal populations - Large samples results

3. Non-parametric methods

3.1 Introduction

3.2 Goodness-of-fit test

3.3 Independence test

4. Linear regression model

4.1 Introduction

4.2 Definition of the linear regression model

4.3 Basic hypotheses of the model

4.4 Coefficient estimation through the least squares method

4.5 Goodness-of-fit assessment

4.6 The normal linear regression model

4.7 Inference in the linear regression model

5. Further topics in the linear regression model

5.1 Heteroskedasticity

5.2 Specification

5.3 Prediction