Statistics I

Statistics I

News:

• The Statistics I Exam inspection will take place on Thursday, April 18 at 08:15 in room G302
• Note: The first lecture takes place on Oct 23^rd
• The lectures and tutorials are planned as on-campus sessions.
• Note: Sign-up for this course on ZEUS. 
• Further information and course material will be provided on ILIAS .

Instructor: Prof. Dr. Ralf Brüggemann

Time and Room:

Time:  Monday,  13:30 - 15:00

Room: Konzil1

Language:

Lectures and tutorials are in English.

Prerequisites:

College-level background in calculus including univariate integration and differentiation, partial differentiation, and multivariate integration

Tutorials:

Course Description:

The lecture offers an introduction to statistical analysis. Topics covered include univariate and multivariate descriptive methods, explorative methods, probability, discrete and continuous random variables and their distributions. Tutorials complement the lecture and include a discussion of output from the statistical software STATA. This lecture is typically offered in winter terms.

Course Outline:

1. 1. Introduction and Basic Statistical Concepts

1.1. What is „Statistics“?

1.2. Statistical Units

1.3. Characteristics and Values of Characteristics

1.4. Statistical Variables

1.5. Types of Characteristics

2. Data and Univariate Descriptive Statistics

2.1. Frequency Tables

2.2. Graphical Methods for Summarizing Data

2.3. Cumulative Frequency Distribution and Empirical Cumulative Distribution Function

2.4. Empirical Measures of Location and Dispersion

2.5. Empirical Measures of Concentration

3. Multivariate Description and Exploration

3.1. Two-way Tables, Margin Counts and Conditional Frequencies

3.2. Scatterplots

3.3. Empirical Correlations

4. Probability

4.1. Definitions of Probabilities

4.2. Interpretation of Probabilities

4.3. Random Samples and Combinations

4.4. Conditional Probability

4.5. Independence

4.6. Law of Total Probability

4.7. Bayes’ Theorem

5. Discrete Random Variables

5.1. Distributions and Parameters of Discrete Random Variables

5.2. Examples of Discrete Distributions

6. Continuous Random Variables

6.1. Definition and Parameters of Continuous Distributions

6.2. Examples of Continuous Distributions

7. Multivariate Random Variables

7.1. Definition of Multivariate Random Variables

7.2. Bivariate Discrete and Continuous Random Variables

7.3. Independence of Random Variables

7.4. Covariance and Correlation

7.5. Bivariate Normal Distribution

Readings:

• Wackerly, D. D., Mendenhall, W. & Scheaffer, R. L. (2008), Mathematical Statistics with Applications (7. edn.: Brooks/Cole Cengage)

• Further resources to be discussed in class.

Software:

• Printouts from the statistical software R will be used in some of the tutorials.

Course Material and Information:

• via ILIAS
• via ZEUS (The Campus Management team is offering new students an introductory session on how to use ZEUS. Further information can be found here. You can register for this one-time session here.)