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Statistiek Voor Bedrijfswetenschappen KULeuven Schakeljaar Handelswetenschappen

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  • Course
  • Statistiek Voor Bedrijfswetenschappen (Y50234)
  • Institution
  • Katholieke Universiteit Leuven (KU Leuven)

Dit document bevat volledige en duidelijke notities van alle lessen van het vak Statistiek voor Bedrijfswetenschappen van het Schakeljaar Handelswetenschappen gegeven door Patrick Wessa in KULeuven Antwerpen. Ik behaalde op mijn examen in januari 2023 (eerste examenkans) 12/20

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Document information

  • February 18, 2023
  • 183
  • 2022/2023
  • Class notes
  • Patrick wessa
  • All classes

Subjects

  • statistiek
  • schakeljaar
  • handelswetenschappen
  • kuleuven
  • notities
  • college
  • aantekeningen
  • patrick wessa
  • 2022 2023
  • kul
  • samenvatting

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  • Katholieke Universiteit Leuven (KU Leuven)
  • Schakeljaar Handelswetenschappen
  • Statistiek Voor Bedrijfswetenschappen (Y50234)
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Statistiek voor bedrijfswetenschappen
QQ-plot komt altijd voor op het examen

Inhoudsopgave
1 hoofdstuk 1: getting started ........................................................................................................... 5
1.1 R Framework for Statistical Computing .................................................................................. 5
2 hoofdstuk 2: introduction to probability ........................................................................................ 6
2.1 Defenition of probability ........................................................................................................ 6
2.2 Jeffreys’ axiom system............................................................................................................ 7
2.2.1 Axiom 1: comparability – vergelijkbaarheid ................................................................... 7
2.2.2 axiom 2: transitivity - transitiviteit .................................................................................. 7
2.2.3 axiom 3: deducibility – deduceerbaarheid...................................................................... 7
2.3 Stelling van Bayes ................................................................................................................... 8
2.3.1 theorie ............................................................................................................................ 8
2.3.2 Voorbeeld ..................................................................................................................... 10
2.3.3 specificiteit en de sesitiviteit ........................................................................................ 11
2.4 Multinomial Naive Bayes Classifier ....................................................................................... 12
2.4.1 voorbeeld ..................................................................................................................... 12
2.4.2 interactie effect ............................................................................................................ 14
2.4.3 Zero Probabilities .......................................................................................................... 15
2.4.4 Types of Naive Bayes Classifiers ................................................................................... 15
2.4.5 Wet van de grote getallen ............................................................................................ 16
2.4.6 Voorbeeld om het uit te leggen .................................................................................... 16
3 hoofdstuk 3: waarschijnlijkheidsverdelingen ............................................................................... 19
3.1 beschrijvende statistieken .................................................................................................... 19
3.2 discrete waarschijnlijkheidsverdeling ................................................................................... 20
3.2.1 bernoulli verdeling ........................................................................................................ 20
3.2.2 binomiaal verdeling ...................................................................................................... 21
3.2.3 multinominiaal verdeling .............................................................................................. 24
3.3 continue verdelingen ............................................................................................................ 25
3.3.1 uniforme verdeling ....................................................................................................... 25
3.3.2 de normale verdeling = gausse verdeling ..................................................................... 27
3.3.3 willekeurige verdeling ................................................................................................... 32
RStudio ................................................................................................................................................. 35
3.3.4 Gaussian naive bayes classifier ..................................................................................... 40
3.3.5 Chi verdeling ................................................................................................................. 44

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, 3.3.6 Chi kwadraat verdeling (1 parameter) .......................................................................... 44
3.3.7 Chi kwadraat verdeling (2 parameters) ........................................................................ 47
3.3.8 student t-verdeling ....................................................................................................... 47
3.3.9 fisher f-verdeling........................................................................................................... 49
3.4 conclusies ............................................................................................................................. 49
4 hoofdstuk 4: Beschrijvende statistiek en exploratieve gegevensanalyse ..................................... 51
4.1 types of data ......................................................................................................................... 51
4.1.1 kwalitatieve data .......................................................................................................... 51
4.1.2 kwantitatieve data ........................................................................................................ 51
4.2 kwalitatieve data .................................................................................................................. 51
4.2.1 frequency plot (bar plot)............................................................................................... 51
4.2.2 frequentietabel ............................................................................................................. 52
4.2.3 contingentie tabel......................................................................................................... 53
4.2.4 Binonomial classification metrics ................................................................................. 53
4.3 kwantitatieve data ................................................................................................................ 55
4.3.1 stem-and-leaf plot ........................................................................................................ 55
4.3.2 histogram...................................................................................................................... 56
4.3.3 Quantiles/ kwantielen .................................................................................................. 60
4.3.4 central tendency ........................................................................................................... 64
4.3.5 Variabiliteit ................................................................................................................... 70
4.3.6 Skewness en kurtosis .................................................................................................... 74
4.3.7 concentratiemaatstaven ............................................................................................... 78
4.3.8 notched boxplot ........................................................................................................... 78
4.3.9 Scatterplot .................................................................................................................... 80
4.3.10 pearson correlatie ........................................................................................................ 81
4.3.11 rank correlatie .............................................................................................................. 85
4.3.12 partiële pearson correlatie ........................................................................................... 86
4.3.13 simple linear regression ................................................................................................ 90
4.3.14 momenten .................................................................................................................... 90
4.3.15 Kwantiel-kwantielplot (QQ-plot)................................................................................... 91
4.3.15 Kwantiel-kwantielplot (QQ-plot)................................................................................... 92
4.3.16 Probability Plot Correlation Coefficient Plot (PPCC- plot) ............................................. 98
4.3.17 kernel density estimation ............................................................................................. 99
4.3.18 bivariate Kernel Density Plot ........................................................................................ 99
4.3.19 Bootstrap Plot (central tendency)............................................................................... 100
4.3.20 survey scores rank order comparison ......................................................................... 102

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, 4.3.21 cronbach alpha ........................................................................................................... 105
4.4 kwantitatieve gegevens met tijdsdimensie/ tijdreeksen .................................................... 106
4.4.1 Equi-distante tijdreeksen ............................................................................................ 106
4.4.2 time series plot (run sequence plot ............................................................................ 107
4.4.3 mean plot ................................................................................................................... 107
4.4.4 blocked bootstrap plot (central tendency) ................................................................. 110
4.4.5 standaard deviation-mean plot .................................................................................. 111
4.4.6 Variatie reduction matrix ............................................................................................ 112
4.4.7 (partiële) autocorrelatie functie ................................................................................. 113
4.4.8 Periodogram en cumulatief periodogram .................................................................. 114
5 hoofdstuk 5: Hypothese testen .................................................................................................. 120
5.1 the central limit theorem ................................................................................................... 121
5.2 Statistische toets van het populatiegemiddelde met bekende variantie (veronderstelling)
121
5.2.1 voorbeeld: Statistische hypothese: Testen van het gemiddelde met bekende variantie -
Voorbeeld 1: Kritische waarde (Regio) ....................................................................................... 124
5.2.2 Voorbeeld: Statistische hypothese: Testen van het gemiddelde met bekende variantie -
Voorbeeld 2: P-waarde (waarschijnlijkheid ................................................................................ 124
5.3 Hypothesetests voor onderzoeksdoeleinden ..................................................................... 125
5.3.1 één steekproef t-Test/ one sample t-test ................................................................... 125
5.3.2 Skewness & kurtosis test ............................................................................................ 129
5.3.3 Gepaarde twee-steekproef t-Test............................................................................... 131
5.3.4 WILCOXON SIGNED-rank test ..................................................................................... 133
5.3.5 unpaird two sample t-test .......................................................................................... 134
5.3.6 unpaired two sample welch test ................................................................................. 137
5.3.7 mann-whitney u test (wilcoxon rank-sum test) .......................................................... 138
5.3.8 bayesian two sample test ........................................................................................... 139
5.3.9 Chi-squared tests for count data ................................................................................ 139
5.3.10 one way analysis of variance (1-way anova) ............................................................... 142
5.3.11 two way analysis of variance (2-way anova) .............................................................. 144
6 hoofdstuk 6: regressie modellen ................................................................................................ 148
6.1 Eenvoudig lineair regressiemodel (SLRM) .......................................................................... 148
6.2 Meervoudig lineair regressiemodel (MLRM) ...................................................................... 150
6.3 Hypothesetests met lineaire regressiemodellen (vanuit praktisch perspectief) ................. 151
7 Inleiding tot de analyse van tijdreeksen ..................................................................................... 156
7.1 Case: markt van gezondheids- en persoonlijke verzorgingsproducten (HPC) ..................... 156
7.2 decompositie van een tijdreeks .......................................................................................... 156

3

, 7.2.1 Klassieke decompositie van tijdreeksen door geleidende gemiddelden..................... 156
7.2.2 Seizoensgebonden decompositie van tijdreeksen door loess..................................... 158
7.2.3 Decompositie door structurele tijdreeksmodellen ..................................................... 158
7.3 Ad hoc voorspelling van tijdreeksen ................................................................................... 159
7.3.1 Regressieanalyse van tijdreeksen ............................................................................... 160
7.3.2 Afvlakmodellen/ Smoothing Models .......................................................................... 163
8 hoofdstuk 8: Univariate box-jenkins analyse .............................................................................. 166
8.1 data .................................................................................................................................... 167
8.2 theoretische concepten ...................................................................................................... 168
8.2.1 stationair proces ......................................................................................................... 168
8.2.2 white noice ................................................................................................................. 168
8.3 stationariteit ....................................................................................................................... 168
8.3.1 stationariteit in het gemiddelde ................................................................................. 168
8.3.2 Stationariteit in de variantie ....................................................................................... 169




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