Statistics 2105-EPE-L-D1STAT

The course covers mainly the following aspects:

1. Basic understanding of statistics - the purpose of usage of statistics, when to use statistics, how statistics is used and communicated (e.g. in the media), how to understand the information based on statistics.

2. Basic concepts in statistics - types of variables, sample vs population, estimate vs parameter, descriptive statistics vs inferential statistics.

3. Types of data used in economics - classification wrt the field of economics and wrt to the data structure

4. Basic measures in statistics: measures of central location, measures of dispersion, measures of shape.

5. Visualization of data using appropriate charts, based on the type of data and purpose of analysis

6. Concept of probability distribution function - empirical distribution vs theoretical distribution, properties of normal distribution, histograms and density curves

7. Recognition of descriptive measures based on the graphical respresentation of data (e.g. skewness based on the shape of a histogram)

8. Estimation - understanding of the concept of confidence intervals and significance level

9. Hypothesis testing - rejection and non-rejection of null hypothesis, testing for population proportion vs testing for population mean

10. Measuring dependence - understanding the correlation

11. Brief introduction to regression in MS Excel and basic concepts related with regression (dependent variable vs independent variable, p-value and significance of results)

12. The procedure of statistical analysis - understanding the steps which need to be taken to conduct the effective analysis based on the concepts learned during the course.

In line with the first three introductory lectures students learn the basic tools and functionalities of MS Excel, in order to be able to practice statistics in further classes.
During the course, students will be ongoingly presented with different issues related with data and showed how to deal with typical problems related with statistical analysis.

Term 2025Z:

The course covers mainly the following topics:
1. What is research? Why do we need statistics? When to use statistics? How are statistics used and communicated (e.g., in the media)?

2. Data collection; types of variables; sample vs. population; estimate vs. parameter; descriptive statistics vs. inferential statistics
3. Types of data and data structure.
4. Measures of central tendency, measures of dispersion, measures of shape.
5. Visualization of data using appropriate charts based on data type and purpose; best practices for accurate and effective visual presentation.
6. Recognition of descriptive measures from graphical representation of data (e.g., skewness based on histogram shape); identifying spread and other features from visualizations.
7. Basics of probability calculus. Concept of probability distribution function - empirical distribution vs theoretical distribution, properties of normal distribution, histograms, and density curves
8. Estimation - understanding of the concept of confidence intervals and significance level
9. Hypothesis testing - rejection and non-rejection of null hypothesis, testing for population proportion vs testing for population mean
10. Measuring dependence - understanding the correlation and its strength
11. Brief introduction to regression in MS Excel and basic concepts related to regression (dependent variable vs independent variable, p- value, and significance of results).
12. From the idea to the conclusion. The procedure of statistical analysis
In line with the first three introductory lectures, students learn the basic tools and functionalities of MS Excel, in order to be able to practice statistics in further classes.

Type of course

obligatory courses

Course coordinators

Term 2025Z:

Magdalena Grabowska
Alina Pavelea

Term 2024Z:

Damian Zięba

Learning outcomes

Students understand the purpose of statistics and issues related with how statistics is being communicated to public. (K_W03)
Students understand basic concepts in statistics. (K_W03)
Students know and are able to calculate basic descriptive statistical measures. (K_W03, K_U03)
Students know multiple ways of visualizing statistical data. (K_U02)
Students are able to distinguish between types of data. (K_W03)
Students are able to interpret different types of data. (K_U02)
Students know basic methods for statistical analysis. (K_W03)
Students are able to conduct a basic statistical test. (K_U03)
Students have a basic knowledge of using MS Excel for statistical analysis. (K_U03)
Students are able to do basic data processing using MS Excel. (K_U02)
Students are capable of conducting a simple but effective statistical research. (K_U03)
The student is ready to initiate and participate in projects, identify dilemmas. (K_K02, K_K03)

Assessment criteria

1. Presence during labs (students can miss a maximum of 2 labs during the semester) - precondition to participate in the exam.
2. 30% of pop quiz points - at the beginning of each lab, based on the content covered in the previous lab.
3. 70% of exam points - exam based on multiple-choice questions and open-ended questions. The passing threshold may be decided based
on the distribution of the grades.

Bibliography

Lane, D. M., Scott, D., Hebl, M., Guerra, R., Osherson, D., & Zimmer, H. (2017). An Introduction to Statistics. Rice University. (main textbook)

Moore, D. S., Notz, W. I., & Notz, W. (2006). Statistics: Concepts and controversies. Macmillan. (additional textbook with a lot of graphics and examples).

Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for the behavioral sciences. Cengage Learning. (a bit more advanced)

Term 2025Z:

Lane, D. M., Scott, D., Hebl, M., Guerra, R., Osherson, D., & Zimmer, H. (2017). An Introduction to Statistics. Rice University. (main textbook)
Moore, D. S., Notz, W. I., & Notz, W. (2006). Statistics: Concepts and controversies. Macmillan. (additional textbook with a lot of graphics and examples).
Gravetter, F. J., & Wallnau, L. B. (2016). Statistics for the behavioral sciences. Cengage Learning. (a bit more advanced)

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2105-EPE-L-D1STAT in USOSweb