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 Cursus: 202000556
 202000556Data Analysis I: Introduction to Inferential Statistics
 Cursus informatie Rooster
Cursus202000556
Studiepunten (ECTS)3
CursustypeOnderwijseenheid
VoertaalEngels
Contactpersoondr. H.G. van der Kaap
E-mail-
Docenten
 Examinator dr. H.G. van der Kaap Docent dr. H.G. van der Kaap Contactpersoon van de cursus dr. H.G. van der Kaap
Collegejaar2021
Aanvangsblok
 2A
AanmeldingsprocedureZelf aanmelden via OSIRIS Student
Inschrijven via OSIRISJa
 Cursusdoelen
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } General learning objectives: Students can explain the role of Inferential Statistical in the process of data analysis; Students are able to construct confidence intervals for proportions and means; Students are able to demonstrate the principles of hypothesis testing and can perform by hand and via R different types of tests for means; Students are able to investigate the relationship between two variables by modelling this relationship via regression analysis, choosing a measure for the strength and giving a descriptive interpretation of that relationship.
 Inhoud
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial }   More specific learning objectives: Upon completion of this course, you are able to: explain the role of Inferential Statistical in the process of data analysis and knows what a Sampling Distribution Model is and know what the Central Limit Theorem tells us; construct and interpret confidence intervals for proportions and means; demonstrate the principles of hypothesis testing and can perform by hand and via statistical software tests for means in a one sample, two samples and related samples situation; apply and interpret the principles of hypotheses testing and can explain the risk of making errors when testing hypotheses (type I versus type II); can explain the similarity between a confidence interval and a statistical test, by interpreting the outcome of a confidence interval in terms of a test; select and interpret different measures for the strength of the relationship between two variables given the measurement level of the variables and perform a test for a correlation (by hand and via R); model, execute and interpret a linear relationship between two variables via (simple) regression on a descriptive level (by hand and via a statistical program); analyse, evaluate and interpret the statistical and practical implications of the outcomes of a regression analysis, plus analysing and interpreting residuals, confidence intervals and prediction intervals for the expected outcomes for specific values of the independent variable(s).
Voorkennis
 Knowledge: Basic understanding of probability and statistics; Basic level of understanding of algebra and calculus. Skills: Basic Excel skills: Entering formulas, using simple mathematical functions, copying formulas, errors in formulas, spreadsheet formatting, making graphs; Sufficient language skills in English
Voorkennis kan worden opgedaan met
 Knowledge: According to the ‘eindtermen Wiskunde A’, all students should have this knowledge*. Skills: High school, TOP module, or BOM module.
 Participating study
 Module
 Module 3
Verplicht materiaal
Course material
 Study material is made available through Canvas.
Aanbevolen materiaal
-
Werkvormen
Assessment
 Aanwezigheidsplicht Ja

Hoorcollege

Project begeleid
 Aanwezigheidsplicht Ja

Project onbegeleid
 Aanwezigheidsplicht Ja

Werkcollege

Zelfstudie geen begeleiding
 Aanwezigheidsplicht Ja

Toetsen
 Data analysis I: descriptive statisticsOpmerking4 (sub)assignments and 1 written test (assignment 20%, test 80%)
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