contents

0. SOFTWARE r - BRIEF INTRODUCTION

1. PROBABILITY 

Conditional probability. Multiplication Rule. Independent events.

2. PROBABILITY DISTRIBUTIONS

Notion of random variable
Discrete random variable. Probability and distribution functions. Mean value and
variance. Properties
Binomial and Poisson Distributions
Continuous random variable. Probability and distribution functions. Mean value
and variance. Properties
Uniform, Exponential and Normal Distributions
Central Limit Theorem

3. SAMPLING 

Population and sample
Random sample
Distribution of the sample mean
Sample proportion

4. PARAMETER ESTIMATION

Confidence intervals for mean and differences of means.
Confidence intervals for proportions and difference of proportions

5. Hypotheses testing

Tests for mean, difference of means, proportions and difference of proportions

6. linear regression

Estimation and inference of linear regression parameters using the least squares method