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Explanation and Summary - Statistics instruction lectures

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The author passed the test with a 8.5. This summary gives you a good overview of everything that has been discussed during the video lectures from . Everything is exam material. Clear overview and explanation of the formulas and calculations that you must be able to take for the test. No unnecessary difficulties. The author of the article has been to 98% of the lectures, case lectures and FAQs or has looked back and co-written, made all assignments and checked them and 85% of the SPSS trial exam was correct in one go. The summary is for the most part in English, but sometimes notes have been added in Dutch to clarify. Would recommend you to buy this when you are Dutch yourself!

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,Inleiding
This summary gives you a good overview of everything that has been discussed during the lectures
and video lectures from 2019-2020. Everything is exam material.

The author of the article has been to 98% of the lectures, case lectures and FAQs or has looked back
and co-written, made all assignments and checked them and 85% of the SPSS trial exam was correct
in one go.

The summary is for the most part in English, but sometimes notes have been added in Dutch to
clarify. Would recommend you to buy this when you are Dutch yourself!

,Inhoud
Inleiding..................................................................................................................................................2
Overview formula’s................................................................................................................................3
Overview symbols..................................................................................................................................4
Videolecture 1 Descriptive questions: data............................................................................................5
Videolecture 2 A: Basic elements in the process of estimation..............................................................8
Videolecture 2B Confidence interval......................................................................................................9
Videolecture 2C: Hypothesis testing.....................................................................................................12
Videolecture 3A Correlation.................................................................................................................13
Videolecture 3B Cross tables................................................................................................................15
Videolecture 3C Cross tables and elaboration......................................................................................17
VideoLecture 4 Correlations for ordinal and interval variables............................................................18
VideoLecture 5a Differences for means and medians for two interdependent populations
(Male/Female) – (Wilcoxon rank sum test) and can be the same as mann withney............................22
VideoLecture 5b Differences between means and medians for two dependent samples (You have 1
person that scores on autonomy and social orientation). – Wilcoxon signed rank test.......................24
VideoLecture 6A Simple and multiple linear regression analysis..........................................................25
VideoLecture 6B Simple and multiple linear regression analysis (Application)....................................27




Overview formula’s
Standard Error σ / √nn
Standard deviatie (Zie voor uitleg instruction √n (((x1 – μ) ) 2 + (x2 – μ) ) 2 + …):x)

,lecture 1)
Confidence interval x̄ - Z α/2 · (σ / - Z α/2 · (σ / √nn) ≤ μ) ≤ x̄ + Z α/2 · (σ / √n) + Z α/2 · (σ / √nn)
Makkelijker:
x̄ - Z α/2 · (σ / ± Zvalue · SE
Standard error of a proportion √np(1-p)/n
Use the normal approach by confidence interval p±3·√np(1-p)/n
of a proportion
Chi Square ∑((o-e)2/e)
Cramers V Cv = √n (x2/(n-min(c-1)(r-1)) Als je drie rijen hebt
en vier kolommen, reken je dus met het getal 2.
(3-1=2).
Comparing means (interdependent – x̄ - Z α/2 · (σ / 1 - x̄ - Z α/2 · (σ / 2
paramatric)
Comparing medians (interdependent – non- M1 – M 2
parametric)
Comparing means in paired samples Dn = X1n – X2n
Linear simple regression y = β0 + β1*X+ eX+ e
Determination coefficient (R2) R2 = SSM - SST (wordt een getal tussen de 0 en de
1)




Overview symbols
x̄ - Z α/2 · (σ / Sample Mean
μ) Population Mean
α Alpha
p Percentage
X2 ChiSquare
β Regression coefficient (Estimation of the
population slope)
R Pearsons correlation coefficient
Rs Spearmans correlation coefficient
R2 Determination coefficient
SSM Standard error van het model
SST Totale standard error
SSR Residual standard error (Niet te verklaren door
het model)

, Videolecture 1 Descriptive questions: data
Goal: Understand, Calculate and interpret measures of central tendency, variability.

Stephen Toulmin’s model of argumentation
1. Ground: On what data is you conclusion based?
2. Warrant: Why is your choices adequate? (General rules, statistical principles)
3. Claim: What is your decision?

Frequency table: Any variable, any measurement levels.
Central tendency and variability: Depends on the measurement level (Summarizing information)
For example: Mean and Median.

Descriptive static questions: For example: How are the people of the Netherlands spread accross
regions?

3 measures to describe data – Central tendency
Population Sample
Mode (Meest N/O/I/R
voorkomende)
Median (De middelste) M O/I/R
Mean (Gemiddelde) μ x̄ I/R


Variability
Range (Lowest-Highest) O/I/R
IQR IQR IQR O/I/R
Variance σ² s² I/R
Standard deviation σ s I/R

Standard deviation = The mean deviation of all the differences between the observations and the
mean. (You know how tense the values are spread around the mean).




Hoe reken je de standard deviatie uit?

Stap 1. Trek alle scores af van het gemiddelde. (x 1 – μ) ) + (x2 – μ) ) + …
Stap 2. Doe alle antwoorden in het kwardraat. (x 1 – μ) ) 2 + (x2 – μ) ) 2 + …
Stap 3. Deel het antwoordt door de hoeveel heid observaties. ((x 1 – μ) ) 2 + (x2 – μ) ) 2
+ …):x
Stap 4. Doe de wortel daarvan. √n (((x 1 – μ) ) 2 + (x2 – μ) ) 2 + …):x)

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