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Inferential Statistics

At the end of the course, candidates will be able to, in general terms:

More specifically students will be able to:

Assumed previous knowledge

It is assumed students are very well versed in the distinction between units and variables; the measurement levels of variables (dichotomous, nominal, scale); the main ‘statistics’ describing variables (‘mean’, ‘standard deviation’ and ‘variance), the ‘standardization’ of variables, and with the (standardized) normal distribution (and the associated ‘empirical rule’). These topics are covered in the course Research Methods and Descriptive Statistics.

Content

In this course the basic notions of data analysis are introduced that would allow to make inferences about populations on the basis of a randomly sampled data set. The course uses the regression (or ‘linear’) model as the basic skeleton and in this context introduces confidence intervals and tests. In addition, it familiarizes students with the logic and implementation of some non-parametric statistical analyses (methods that do not use a concepts like ‘the mean’ and ‘variance’). Usage of these methods is illustrated using research examples. The software used in both teaching and in the assessment is R for statistics.

Assignments and exams

The assessment in this course consists of some assignments and two written exams.
The assignments count for 20% of the final grade, while the exams both count for 40% of the final mark.
The minimum mark for an exam must be at least 5.0.
The individual assignments are mandatory. They are only accepted as a ‘valid attempt’, if you try to seriously answer all questions in the assignments and hand in the assignment before the deadline. There is no minimum grade for the assignments though. If you do not make all assignments and hand them in before the deadline, you will not be allowed to take part in the written exams.
The final grade of the course should be at least a 5.5.

For both partial exams a retake will be offered.
For the assignments there is no graded retake, although you are allowed to repair the omission to hand in a valid assignment by handing in a repair assignment for which you will not get points. 

Time Table

PhDs can choose one of the 3 tutorial groups: 

Start week (ISO)

Start

End

Duration

Type

Location(s)

Note

46

Monday, 14 November 2022, 13:45

Monday, 14 November 2022, 15:30

1:45

Lecture

HR C101 (250)


46

Thursday, 17 November 2022, 08:45

Thursday, 17 November 2022, 10:30

1:45

Tutorial

NH 124 (75)


46

Thursday, 17 November 2022, 10:45

Thursday, 17 November 2022, 12:30

1:45

Tutorial

CR 2K (84)


46

Thursday, 17 November 2022, 13:45

Thursday, 17 November 2022, 15:30

1:45

Tutorial

RA 2334 (80)


47

Monday, 21 November 2022, 13:45

Monday, 21 November 2022, 15:30

1:45

Lecture

WA 1 (477)


48

Monday, 28 November 2022, 13:45

Monday, 28 November 2022, 15:30

1:45

Lecture

WA 1 (477)


48

Thursday, 1 December 2022, 08:45

Thursday, 1 December 2022, 10:30

1:45

Tutorial

RA 2334 (80)


48

Thursday, 1 December 2022, 10:45

Thursday, 1 December 2022, 12:30

1:45

Tutorial

OH 113 (80)


48

Thursday, 1 December 2022, 13:45

Thursday, 1 December 2022, 15:30

1:45

Tutorial

NH 115 (75)


49

Monday, 5 December 2022, 13:45

Monday, 5 December 2022, 15:30

1:45

Lecture

WA 1 (477)


49

Thursday, 8 December 2022, 08:45

Thursday, 8 December 2022, 10:30

1:45

Tutorial

NH 124 (75)


49

Thursday, 8 December 2022, 10:45

Thursday, 8 December 2022, 12:30

1:45

Tutorial

NH 124 (75)


49

Thursday, 8 December 2022, 13:45

Thursday, 8 December 2022, 15:30

1:45

Tutorial

OH 111 (80)


50

Thursday, 15 December 2022, 10:45

Thursday, 15 December 2022, 12:30

1:45

Seminar

WA 2 (307)

Topic: exam part 1.

50

Friday, 16 December 2022, 13:45

Friday, 16 December 2022, 16:15

2:30

Exam

Therm 1 (115), Therm 2 (115)

Part 1.

51

Monday, 19 December 2022, 13:45

Monday, 19 December 2022, 15:30

1:45

Lecture

WA 1 (477)


51

Thursday, 22 December 2022, 08:45

Thursday, 22 December 2022, 10:30

1:45

Tutorial

TL 3138 (90)


51

Thursday, 22 December 2022, 10:45

Thursday, 22 December 2022, 12:30

1:45

Tutorial

NH 124 (75)


51

Thursday, 22 December 2022, 13:45

Thursday, 22 December 2022, 15:30

1:45

Tutorial

NH 115 (75)


2

Monday, 9 January 2023, 13:45

Monday, 9 January 2023, 15:30

1:45

Lecture

WA 1 (477)


2

Thursday, 12 January 2023, 08:45

Thursday, 12 January 2023, 10:30

1:45

Tutorial

TL 3138 (90)


2

Thursday, 12 January 2023, 10:45

Thursday, 12 January 2023, 12:30

1:45

Tutorial

TL 3138 (90)


2

Thursday, 12 January 2023, 13:45

Thursday, 12 January 2023, 15:30

1:45

Tutorial

CR 3C (94)


2

Friday, 13 January 2023, 10:45

Friday, 13 January 2023, 12:30

1:45

Other

CR 2K (84)

Exam review. Exam Inferential Statistics (Part 1) of Friday December 16, 2022.

3

Tuesday, 17 January 2023, 10:45

Tuesday, 17 January 2023, 12:30

1:45

Lecture

WA 1 (477)


3

Thursday, 19 January 2023, 08:45

Thursday, 19 January 2023, 10:30

1:45

Tutorial

NH 124 (75)


3

Thursday, 19 January 2023, 10:45

Thursday, 19 January 2023, 12:30

1:45

Tutorial

NH 124 (75)


3

Thursday, 19 January 2023, 13:45

Thursday, 19 January 2023, 15:30

1:45

Tutorial

CR 3C (94)


3

Friday, 20 January 2023, 13:45

Friday, 20 January 2023, 16:15

2:30

Exam

Therm 2 (115)

Resit. Part 1.

4

Monday, 23 January 2023, 13:45

Monday, 23 January 2023, 15:30

1:45

Lecture

WA 1 (477)


4

Thursday, 26 January 2023, 10:45

Thursday, 26 January 2023, 12:30

1:45

Seminar

HR C101 (250)

Topic: exam part 2.

4

Friday, 27 January 2023, 13:45

Friday, 27 January 2023, 16:15

2:30

Exam

Therm 1 (115), Therm 2 (115)

Part 2.


  • Programme is for

    PhDs

  • ECTS

    ?

  • Location

    at the campus

dr. H. van der Kolk (Henk)
Associate Professor
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