SAMENVATTING
GZW1026
Introductie Statistiek
Universiteit Maastricht
2025–2026
,Inhoudsopgave
Seminar 1.1 ..................................................................................................................................................................................................... 3
Types of variables ..................................................................................................................................................................................................................... 3
Histogram en bar chart .......................................................................................................................................................................................................... 4
Examentip: bar chart = categorische variabele. Histogram = numerieke variabele. Dit verschil moet je echt automatisch
herkennen. .................................................................................................................................................................................................................................. 5
Types of graphs: bar chart, boxplot, histogram en scatter plot............................................................................................................................. 5
Measures of central tendency: mean, median en mode........................................................................................................................................... 7
Measures of variability: variance, standard deviation en IQR................................................................................................................................ 9
Boxplots ...................................................................................................................................................................................................................................... 10
Theoretic distributions: symmetric en skewed ........................................................................................................................................................... 11
Z-score ........................................................................................................................................................................................................................................ 14
Seminar 1.2 ................................................................................................................................................................................................... 15
Measure of association: Pearson correlation.............................................................................................................................................................. 15
Association and simple linear regression ...................................................................................................................................................................... 16
Dependent/independent variables .................................................................................................................................................................................. 17
Interpretation regression line, effect of X on Y ........................................................................................................................................................... 17
Predicted values ...................................................................................................................................................................................................................... 18
Residual ...................................................................................................................................................................................................................................... 18
R-square ..................................................................................................................................................................................................................................... 19
Seminar 2.1 ................................................................................................................................................................................................... 21
De 2x2-tabel ............................................................................................................................................................................................................................. 21
Probability, odds, risk difference, relative risk en odds ratio ................................................................................................................................ 22
Chi-square test of independence ...................................................................................................................................................................................... 23
Seminar 2.2 ................................................................................................................................................................................................... 25
Population, sample and sampling distribution ........................................................................................................................................................... 25
Central Limit Theorem .......................................................................................................................................................................................................... 26
Standard error of an estimate/ SD of a sampling distribution ............................................................................................................................. 26
Confidence interval ................................................................................................................................................................................................................ 27
One sample problem ............................................................................................................................................................................................................. 28
Seminar 3.1 ................................................................................................................................................................................................... 30
Null/alternative hypothesis (H0/Ha) ................................................................................................................................................................................ 30
P-value (SPSS: Sig. (2-tailed)) ............................................................................................................................................................................................. 31
Z-test en t-test (one sample) .............................................................................................................................................................................................. 32
Type I- en Type II-error (α en β) en power .................................................................................................................................................................... 32
Seminar 3.2 ................................................................................................................................................................................................... 34
Z-test en t-test (one sample) .............................................................................................................................................................................................. 34
t-test (two samples) .............................................................................................................................................................................................................. 35
, t-test (paired samples) ......................................................................................................................................................................................................... 36
Test statistic.............................................................................................................................................................................................................................. 36
Seminar 4.1 ................................................................................................................................................................................................... 38
Testing regression coefficients for simple linear regression .................................................................................................................................. 38
Comparing regression and two-sample t-test ............................................................................................................................................................ 39
Always plot your data ........................................................................................................................................................................................................... 40
Checking assumptions .......................................................................................................................................................................................................... 40
Seminar 4.2 ................................................................................................................................................................................................... 42
Chi-square test......................................................................................................................................................................................................................... 42
Begrippenlijst ................................................................................................................................................................................................ 46
Formularium ................................................................................................................................................................................................. 51
Overzicht van symbolen...................................................................................................................................................................................................... 51
Seminar 1.1 - Descriptive statistics for one variable ............................................................................................................................................. 51
Seminar 1.2 - Correlation and simple linear regression ...................................................................................................................................... 52
Seminar 2.1 - Association between qualitative variables .................................................................................................................................... 52
Seminar 2.2 - Sampling distribution and confidence interval ........................................................................................................................... 53
Seminar 3.1 and 3.2 - Hypothesis testing and t-tests ............................................................................................................................................. 53
Seminar 4.1 and 4.2 - Regression coefficients and chi-square........................................................................................................................... 54
Snelle keuzehulp: welke maat of techniek gebruik je? .......................................................................................................................................... 54
, Seminar 1.1
Descriptive statistics for one variable
Types of variables
In statistiek begin je bijna altijd met de vraag: met welk soort variabele werk ik? Dat bepaalt namelijk welke grafiek,
welke samenvatting en welke statistische test je later mag gebruiken.
Een variabele is een kenmerk dat kan verschillen tussen personen, objecten of metingen. Voorbeelden zijn
geslacht, leeftijd, BMI, inkomen, gewicht, opleidingsniveau of rookstatus.
Figuur 1. Overzicht van de belangrijkste types variabelen.
Categorical/kwalitatieve variabelen
Een categorische variabele deelt mensen of observaties in groepen in. De waarden zijn vooral labels of categorieën.
Je telt dan hoeveel personen in elke categorie vallen.
Nominaal
Bij nominale variabelen is er geen natuurlijke volgorde tussen de categorieën. De categorieën zijn gewoon namen
of labels. Je kan dus wel tellen hoeveel personen of observaties in elke categorie vallen, maar je kan er niet logisch
mee rekenen. Daarom bereken je bij nominale variabelen meestal geen mean of median, omdat de categorieën
geen rekenkundige betekenis hebben.
Voorbeelden zijn geslacht, bloedgroep, haarkleur, land van geboorte en rookstatus met de categorieën never, past
en current.
Ordinaal
Bij ordinale variabelen is er wel een natuurlijke volgorde tussen de categorieën, maar je weet niet precies hoe
groot het verschil tussen die categorieën is. Je kan dus zeggen dat de ene categorie hoger of lager is dan de andere,
maar niet of de afstanden tussen de categorieën even groot zijn. Daarom kan de mediaan soms zinvol zijn, omdat
je naar een middelste categorie kan kijken. Het gemiddelde is vaak minder logisch, omdat de categorieën geen
exacte numerieke afstand hebben.
Voorbeelden zijn opleidingsniveau, tevredenheidsscore, pijnscore in categorieën, een Likert-schaal en koffiegrootte
zoals small, medium en large.
GZW1026
Introductie Statistiek
Universiteit Maastricht
2025–2026
,Inhoudsopgave
Seminar 1.1 ..................................................................................................................................................................................................... 3
Types of variables ..................................................................................................................................................................................................................... 3
Histogram en bar chart .......................................................................................................................................................................................................... 4
Examentip: bar chart = categorische variabele. Histogram = numerieke variabele. Dit verschil moet je echt automatisch
herkennen. .................................................................................................................................................................................................................................. 5
Types of graphs: bar chart, boxplot, histogram en scatter plot............................................................................................................................. 5
Measures of central tendency: mean, median en mode........................................................................................................................................... 7
Measures of variability: variance, standard deviation en IQR................................................................................................................................ 9
Boxplots ...................................................................................................................................................................................................................................... 10
Theoretic distributions: symmetric en skewed ........................................................................................................................................................... 11
Z-score ........................................................................................................................................................................................................................................ 14
Seminar 1.2 ................................................................................................................................................................................................... 15
Measure of association: Pearson correlation.............................................................................................................................................................. 15
Association and simple linear regression ...................................................................................................................................................................... 16
Dependent/independent variables .................................................................................................................................................................................. 17
Interpretation regression line, effect of X on Y ........................................................................................................................................................... 17
Predicted values ...................................................................................................................................................................................................................... 18
Residual ...................................................................................................................................................................................................................................... 18
R-square ..................................................................................................................................................................................................................................... 19
Seminar 2.1 ................................................................................................................................................................................................... 21
De 2x2-tabel ............................................................................................................................................................................................................................. 21
Probability, odds, risk difference, relative risk en odds ratio ................................................................................................................................ 22
Chi-square test of independence ...................................................................................................................................................................................... 23
Seminar 2.2 ................................................................................................................................................................................................... 25
Population, sample and sampling distribution ........................................................................................................................................................... 25
Central Limit Theorem .......................................................................................................................................................................................................... 26
Standard error of an estimate/ SD of a sampling distribution ............................................................................................................................. 26
Confidence interval ................................................................................................................................................................................................................ 27
One sample problem ............................................................................................................................................................................................................. 28
Seminar 3.1 ................................................................................................................................................................................................... 30
Null/alternative hypothesis (H0/Ha) ................................................................................................................................................................................ 30
P-value (SPSS: Sig. (2-tailed)) ............................................................................................................................................................................................. 31
Z-test en t-test (one sample) .............................................................................................................................................................................................. 32
Type I- en Type II-error (α en β) en power .................................................................................................................................................................... 32
Seminar 3.2 ................................................................................................................................................................................................... 34
Z-test en t-test (one sample) .............................................................................................................................................................................................. 34
t-test (two samples) .............................................................................................................................................................................................................. 35
, t-test (paired samples) ......................................................................................................................................................................................................... 36
Test statistic.............................................................................................................................................................................................................................. 36
Seminar 4.1 ................................................................................................................................................................................................... 38
Testing regression coefficients for simple linear regression .................................................................................................................................. 38
Comparing regression and two-sample t-test ............................................................................................................................................................ 39
Always plot your data ........................................................................................................................................................................................................... 40
Checking assumptions .......................................................................................................................................................................................................... 40
Seminar 4.2 ................................................................................................................................................................................................... 42
Chi-square test......................................................................................................................................................................................................................... 42
Begrippenlijst ................................................................................................................................................................................................ 46
Formularium ................................................................................................................................................................................................. 51
Overzicht van symbolen...................................................................................................................................................................................................... 51
Seminar 1.1 - Descriptive statistics for one variable ............................................................................................................................................. 51
Seminar 1.2 - Correlation and simple linear regression ...................................................................................................................................... 52
Seminar 2.1 - Association between qualitative variables .................................................................................................................................... 52
Seminar 2.2 - Sampling distribution and confidence interval ........................................................................................................................... 53
Seminar 3.1 and 3.2 - Hypothesis testing and t-tests ............................................................................................................................................. 53
Seminar 4.1 and 4.2 - Regression coefficients and chi-square........................................................................................................................... 54
Snelle keuzehulp: welke maat of techniek gebruik je? .......................................................................................................................................... 54
, Seminar 1.1
Descriptive statistics for one variable
Types of variables
In statistiek begin je bijna altijd met de vraag: met welk soort variabele werk ik? Dat bepaalt namelijk welke grafiek,
welke samenvatting en welke statistische test je later mag gebruiken.
Een variabele is een kenmerk dat kan verschillen tussen personen, objecten of metingen. Voorbeelden zijn
geslacht, leeftijd, BMI, inkomen, gewicht, opleidingsniveau of rookstatus.
Figuur 1. Overzicht van de belangrijkste types variabelen.
Categorical/kwalitatieve variabelen
Een categorische variabele deelt mensen of observaties in groepen in. De waarden zijn vooral labels of categorieën.
Je telt dan hoeveel personen in elke categorie vallen.
Nominaal
Bij nominale variabelen is er geen natuurlijke volgorde tussen de categorieën. De categorieën zijn gewoon namen
of labels. Je kan dus wel tellen hoeveel personen of observaties in elke categorie vallen, maar je kan er niet logisch
mee rekenen. Daarom bereken je bij nominale variabelen meestal geen mean of median, omdat de categorieën
geen rekenkundige betekenis hebben.
Voorbeelden zijn geslacht, bloedgroep, haarkleur, land van geboorte en rookstatus met de categorieën never, past
en current.
Ordinaal
Bij ordinale variabelen is er wel een natuurlijke volgorde tussen de categorieën, maar je weet niet precies hoe
groot het verschil tussen die categorieën is. Je kan dus zeggen dat de ene categorie hoger of lager is dan de andere,
maar niet of de afstanden tussen de categorieën even groot zijn. Daarom kan de mediaan soms zinvol zijn, omdat
je naar een middelste categorie kan kijken. Het gemiddelde is vaak minder logisch, omdat de categorieën geen
exacte numerieke afstand hebben.
Voorbeelden zijn opleidingsniveau, tevredenheidsscore, pijnscore in categorieën, een Likert-schaal en koffiegrootte
zoals small, medium en large.
