Basics of Inferential Statistics using IBM SPSS

elective courses

The overarching aim of this course is to provide participants with the tools necessary to use inferential statistics to obtain reliable empirical results. Participants will be able to (1) assess the data, (2) run the most popular tests to compare groups, (3) run correlations and simple regressions.

Overall objectives:

Participants will:

1. understand the importance of a well-structured research design for data analysis;

2. learn how to visualise and run diagnostic data analysis to ensure the use of an appropriate statistical test;

3. learn how to deal with problems with the data;

4. learn how to clearly report results from statistical analysis;

5. become familiar with different types of tests and their suitability to different analyses;

6. be able to search for and identify reliable sources of information on different statistical tests.

When conducting studies, researchers often collect numerical data to answer certain questions and/or to test certain hypotheses. The data collected always tell a story, but this story becomes far more interesting when it is possible to generalize your findings. That is, when it is possible to claim that the results obtained in your study can be generalised to the broader population. What is more interesting? To be able to say that 1) teaching method A works better than teaching method B in the group of 50 students that you investigated, or 2) that method A works better than method B in general, among Polish students? The second option is a much more useful finding. However, to be able to claim this, one needs statistics. And fortunately, statistical software now does all the calculation for reserachers.

This course aims to introduce participants to the basics of inferential statistics using IBM SPSS, a popular statistical software. The course is mostly practical, focused on checking data, organising data, and using the software, running statistical analyses. However, some theoretical discussions are needed, especially at the beginning of the course. Please note that no background in statistics is needed, and only a basic understanding of maths is expected.

The topics covered in the course will be the following:

1. The importance of statistics

2. Variables and organizing data

3. The SPSS interface

4. Test assumptions and running data diagnostics

5. Comparing two means (t tests and nonparametric alternatives)

6. Comparing two or more means (ANOVAs and nonparametric alternatives).

7. Correlations

8. Simple and multiple linear regressions

9. The assumptions of linear regressions

10. Diagnosing residuals and spotting outliers

Education at language level B2+

The course is mostly practical, and any needed theoretical material will be provided. The list below refer to books that may be useful should participants intend to explore the topics further.

Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th Ed.). Los Angeles: Sage.

Howell, D. C. (2013). Statistical methods for Psychology (8th Edition). Belmont: Wadsworth.

Salkind, N. J., & Frey, B. B. (2019). Statistics for people who (think they) hate statistics (7th Ed.). Los Angeles: Sage.

Knowledge

The participant will:

- understand the importance of a well-structured research design for data analysis;

- understand the data format from common correlational and experimental research designs;

- understand third party research findings.

Skills

The participant will:

- be able to manage the large data sets for future analyses;

- be able to analyse data, check for assumptions in the data, and learn different ways to deal with the assumptions in the data;

- be able to conduct the most common statistical analyses (T-test, ANOVAs, correlations, linear regressions);

- be able to confirm the reliability of the results found;

- be able to report the results of the most common statistical analyses;

- be able to draw conclusions from the data.

Social competencies:

- Listening to others

- Exchanging opinions

- Working in pairs and groups

- Providing and understanding constructive criticism

Education at language level B2+

The final grade is based on:

- practical tasks during the course (50% of the mark).

- The final practical assessment. This will consist of a number of short tasks (50% of the mark).

Attendance: 3 absences are allowed.

If the participant receives an unsatisfactory grade, a second practical assessment (i.e., a second set of short tasks) will be provided.

The form and criteria of the assessment may change depending on the current epidemic situation. Equivalent credit conditions will be established in consultation with the course participants and in accordance with the guidelines in force at the University of Warsaw.