Description

Theory
2

Theory/Practice
2

Instructors

Manel Cruz

Contents

Chapter 1 - Review of Probability: (1week)
a. Probability rules.
b. Multiplication and total probability rules.
c. Bayes Theorem.

Chapter 2 - Distributions of probability. (7 weeks)
a.Random Variable (R.V.).
b.Types of R.V.
c.Probability distributions and probability functions.
d.Mean and variance.
e. Discrete distributions (Binomial and Poisson) and Continuous distributions (uniform, exponential and normal).
f.Additivity
g.Central Limit Theorem

Chapter 3 - Estimation. (3 weeks)
a.Population and sample.
b.Random sample.
c.Sample mean distribution and related items.
d.Sample proportion.
e.Confidence intervals.
f.Significance.
g.Confidence intervals for means, proportions and its variants.

Chapter 4 - Hypothesis Testing. (3 weeks)
a.Statistical hypothesis.
b.Type I and type II errors.
c.Tests on a population mean.
d.Tests on a population proportion.
e.Qui-square tests

Chapter 5 - Regression statistical analysis. (2 weeks)

Learning Outcomes

The mains objectives of this U.C. are to give the students the foundations of probability theory and statistic inference, with a particular weight in methodologies used in data analysis and statistic modeling.
Students will have to disclose knowledge that helps to take decisions and to develop abilities to make forecasts and to formulate judgments in an uncertainty context.

As consequence of the previous item, in the end of the semester the student should:
A.Evaluate probabilities.
B.Identify and handle probabilistic models.
C.Be aware of the random variable definition and understand the main differences between them and deterministic variables.
D.Estimate parameters, make and test statistic hypothesis.
E.Apply linear regression techniques.