6 ECTS credits
180 h study time
Offer 2 with catalog number 1000358ANR for all students in the 1st semester at a (A) Bachelor - preliminary level.
This course offers an overview of descriptive statistics (univariate and bivariate).
Descriptive statistics aims to express the characteristic information which is included in data obtained from (a sample of) a population in numbers, tables and figures.
Relations between 2 (or more) variables can be discovered and estimations (or predictions) can be made.
This course elaborates on the different properties data can have and the different methods which can be used to synthetise and interpret their most important characteristics (measurement scales, graphical representations, parameters of location, spread, symmetry and kurtosis, parameters for bidimensional distributions (like Lambda, covariance and Pearson-, Spearman and Kendall coefficients of correlation), bivariate regression analysis and normal distributions). All theory is explained in lectures. In the seminars and practical exercises the theory is deepened and applied to concrete examples. Calculations in this course are only performed with a calculator.
Continuous and discrete variables
Categorization, Orderability, Distances, Absolute zero point
Measurement scales: nominal, ordinal, interval and ratio scales
Classify variables
1-dimensional distributions
Tables and figures for 1 variable (frequency table, absolute/relative/cumulative frequencies, histogram, frequency polygon, strip chart, box plot, time plots
Summation (symbol)
Frequency distributions in numbers: Characteristic measures
Central tendency (mean, median, mode, geometric and harmonic mean…)
Quantiles
Spread (variance, standard deviation, interquantiles, coefficient of variation, …)
Symmetry and peakiness (Fischer coefficients, central moments, …)
Normal distributions and standard normal distribution
Linear Standard Measures (z and T)
2-dimensional distributions
Relationship between 2 dichotomous variables (from dichotomous to continuous variables)
Scatterplot
Contingency table
lambda coefficient
Relationship between 2 continuous variables
Coefficient of determination
Correlation Coefficients
Regression lines
Linear regression (descriptive): least squares
Relation to t-test
Transform variables for regression
Extrapolation (prediction)
Simpson Paradox
Other (non-parametric) measures of association
Implication versus association
Q coefficient, chi-square, phi coefficient, contingency coefficient
Rank Correlations: Kendall's tau, Gamma, Spearman rank correlation coefficient
All theory is explained in lectures. In the tutoring and practical exercises, the theory is deepened and applied to concrete examples. Calculations in this course are only performed with a calculator.
Study materials, including lecture recordings and slides (Dutch), are made available via CANVAS.
Besides a very thorough knowledge of the theory, it is expected that the student can independently apply the learned techniques to realistic (new) data and use them to solve presented problems.
Based on the presented measurement procedure (e.g. an item with corresponding response scale) indicate the measurement level of the resulting variable and critically take this into account when processing and interpreting obtained data.
To represent given raw data appropriately in a figure.
To prepare a frequency table from raw data.
To prepare a contingency table from given raw data.
To calculate and discuss characteristic values of data.
Be able to determine and interpret regression lines / regression rights.
Be able to apply normal distributions.
The final grade is composed based on the following categories:
Written Exam determines 100% of the final mark.
Within the Written Exam category, the following assignments need to be completed:
Assessment will be by written multiple-choice examination.
The multiple choice exam for this course is scored uising an icreased cesure: in order to compensate for lucky guesses, you are required to have more than half of the questions correct in order to get 10/20. In a 20-question examen with 5 answer options, one is expected to get 4 correct answers by merely lucky guesses. Therefore, you will get 10/20 for the exam only if you also have half of the other 16 questions right (8). So, if you have 12 questions correct, your score for the exam is 10/20; if you have all 20 questions correct, of course, you get 20/20.
Generative AI may not be used in the exam.
This offer is part of the following study plans:
Bachelor of Psychology: Profile Profile Work and Organisational Psychology (only offered in Dutch)
Bachelor of Psychology: Initial track (only offered in Dutch)
Bachelor of Psychology: Profile Profile Clinical psychology (only offered in Dutch)
Bachelor of Adult Education: Profile Social Studies (only offered in Dutch)
Bachelor of Adult Education: Profile Cultural Studies (only offered in Dutch)
Bachelor of Adult Education: Abridged Profile Social Studies (only offered in Dutch)
Bachelor of Adult Education: Initial track (only offered in Dutch)
Bachelor of Adult Education: Abridged Profile Cultural Studies (only offered in Dutch)
Bridging Programme for Master of Science in Educational Sciences: Standaard traject (only offered in Dutch)
Schakelprogramma Master of Science in Educational Sciences: Exchange Ma Economics/Manageme (only offered in Dutch)