93064 - Statistics

Learning outcomes

The goal of this course is to introduce statistics, statistical estimation and testing using basic probability models, random variables and discrete and continuous probability distributions.

Course contents

Descriptive statistics

• Introduction to statistical methodology: types of variables, population vs sample, data matrix.
• Univariate statistics: frequency distributions, organizing and graphing qualitative and quantitative data, arithmetic mean, geometric mean, mode, median, quantiles, measures of variability.
• Statistical ratios and index numbers.
• Bivariate analysis: marginal and conditional frequency distributions, graphical representation of bivariate data, association between two characters, covariance and correlation.
• R tutorials: Introduction R/RStudio, data import, cleaning and data visualization, univariate and bivariate analysis.
  

Statistical inference and regression

• Introduction to probability: experiment, outcomes, sample space.
• Random variables: discrete random variables (the Bernoulli distribution and the binomial), continuous random variables (the normal distribution, the standard normal and Student's t).
• Introduction to statistical inference: population model and parameters, estimators and their sampling distributions, point estimates and confidence intervals for the mean and for the proportion.
• Hypothesis testing: Type I and II errors, significance level, statistical tests for the mean and for the proportion.
• Simple and multiple linear regression: inference for the model coefficients, model checking.
• R tutorials: hypothesis testing and confidence intervals, simple and multiple linear regression.

Readings/Bibliography

Educational material (slides and exercises) on the Virtual Learning Environment platform at the link: https://virtuale.unibo.it.

Suggested texts to complement the slides:

• Cicchitelli, G., D'Urso,  P. ,Minozzo, M. Statistics: Principles and methods, Ediz. Mylab. Pearson (Chapters 1,2,3,4,5,9,10,11,12,13,14,16,17,18,19,20,23).

• Mann, P. S. Introductory statistics, 10th Edition. John Wiley & Sons (only Chapter 14)

Teaching methods

Lectures using slides, R tutorials, problems solved at lessons.

Assessment methods

The exam aims to evaluate students' understanding of the following objectives:

1. knowledge of the statistical statistical descriptive, inferential and regression techniques illustrated during the lectures;
2. ability to use such methods for data analysis;

PARTIAL EXAMS: It is possible to take two partial written exams: students who take the partial exams can accept the grade resulting from the average of the obtained evaluations. The outcome of each individual exam must be at least a pass (>=18).

FINAL EXAM: The exam consists of a written test.

The written tests (PARTIAL AND FINAL) include exercises, multiple choice and open questions and have a variable duration from 90 to 120 minutes. The final vote is expressed in thirtieths. During the written tests it is allowed to use the calculator, the statistical tables and a form that will be made available by the teacher in the teaching material.

Teaching tools

Software: R (http://www.r-project.org/) and RStudio (https://rstudio.com/).

Office hours

See the website of Lucia Guastadisegni