The main objective of Introduction to the Practice of Statistics is to work out the basic concepts of statistics and learn to apply them in practical cases containing statistical data with the use of the computer. To reach this goal, at the end of the course students should:

o Know and apply numerical and graphical tools for data analysis.
o Know the main statistical concepts.
o Use the computer to develop statistical analysis.

Evaluation

o Participation in class: 20 %.
o Assignments during the course: 20 %
o Final comprehensive exam: 60 %.

To get credit for the course a minimum of 40 % has to be obtained in the final exam and a global 50 %.

1
Unit 1: Introduction

Data analysis within statistics. Variables, types and distribution. Histogram, bar diagrams and pie charts.

Unit 2: Graphical and numerical description of distributions (I)

Interpreting histograms. Symmetric and asymmetric distributions. Stemand- leaf diagrams. Time series graphs.

Unit 3: Graphical and numerical description of distributions (II)

Numerical descriptions: mean, median, range, quartiles. Boxplots. Standard deviation. Data transformation.

Unit 4: Normal Distributions

Density curve. Mean and median of a density curve. Properties of the normal distribution. Standard normal distribution. Computations with normal distributions.

Unit 5: Data sets with two variables (I)

Two numerical variables. Scatterplots. Correlation. Regression. Residual analysis. Influential observations. Relation between correlation and regression. Data sets with one numerical and one categorical variable.

Unit 6: Data sets with two variables (II)

Two categorical variables. Contingency tables. Marginal distributions. Bar diagrams. Conditional distributions. Simpson paradox. Textbook: D. Moore, "The Basic Practice of Statistics".