The content covered in this course ranges from elementary reminders in probability, through the construction of confidence intervals, hypothesis tests on parameters such as the mean or the proportion. This last notion is extended to tests of comparisons of means between several populations with the one or two factor ANOVA.

Each document present a summary of the lectures and different exercises.

Lecture 1

The aim of this first session is to motivate the use of statistics in your field of study. It covers a few basic statistical concepts and the properties of the normal distribution.

• Slides Intro.
• Fundamentals

Lecture 2

We are now interested in estimating unknown parameters such as the mean or a proportion parameter by sampling. To do this, we will take a look at confidence interval estimation.

• Sampling Est.

You have to use the following datasets to solve some of the exercises

• Cost Decision
• Speed

Lecture 3

We introduce the concept of hypothesis testing in statistics. This tool will enable us to test hypotheses formulated concerning a parameter relating to the distribution of our data. It is therefore an essential tool for making decisions or drawing conclusions following a study.

• Hypothesis Testing

• ResaleHouse

Lecture 4

The aim is to study the relationship between a quantitative variable and a qualitative variable through analysis of variance. This is a generalization of the case of comparing the means of two groups.

• ANOVA

Homework and Exam

You will find, below, the homework and the exam (similar to the homework) that shall be done to validate this first set of lectures.

• Homework
• Exam