Samenvatting Statistiek Voor Bedrijfswetenschappen (Y50234)
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Course
Statistiek Voor Bedrijfswetenschappen (Y50234)
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Katholieke Universiteit Leuven (KU Leuven)
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Dit is een volledige samenvatting van de cursus en lessen statistiek van het AJ . De cursus staat volledig in het Engels, dit document...
, 4.3.18.10 Voorbeeld ................................................................................................................... 85
4.3.19 Bivariate Kernel Density Plot ............................................................................................ 85
4.3.19.2 R Module ...................................................................................................................... 85
4.3.19.5 Voorbeeld ..................................................................................................................... 86
4.3.20 Bootstrap Plot (voor Central Tendency) ........................................................................... 87
4.3.20.2 R Module ...................................................................................................................... 87
4.3.20.5 Voorbeeld ..................................................................................................................... 91
4.3.21.5 Voorbeeld ..................................................................................................................... 91
4.3.22 Cronbach Alpha ............................................................................................................... 92
4.3.22.2 R Module ...................................................................................................................... 93
4.3.22.5 Voorbeeld ..................................................................................................................... 93
4.4 Kwantitatieve data met tijdsdimensie (tijdreeksen) ................................................................ 94
4.4.1 Equi-distante tijdreeksen .................................................................................................... 94
4.4.2 Tijdreeks Plot ..................................................................................................................... 94
4.4.2.2 R Module ........................................................................................................................ 95
4.4.3. Mean Plot ......................................................................................................................... 95
4.4.3.2. R Module ....................................................................................................................... 96
4.4.4 Blocked Bootstrap Plot (Central Tendency)........................................................................ 99
4.4.4.2 R Module ........................................................................................................................ 99
4.4.4.5 Voorbeeld ....................................................................................................................... 99
4.4.5 Standard Deviation-Mean Plot ........................................................................................... 99
4.4.5.5 Voorbeeld ..................................................................................................................... 100
4.4.6 Variantie reductie matrix .................................................................................................. 101
4.4.6.5 Voorbeeld ..................................................................................................................... 101
4.4.7 Partiële autocorrelatie functie ........................................................................................... 103
4.4.7.5 Voorbeeld ..................................................................................................................... 103
4.4.8 Periodogram .................................................................................................................... 106
4.4.8.5 Voorbeeld ..................................................................................................................... 107
HOOFDSTUK 5: HYPOTHESIS TESTING .................................................................................. 109
5.1.2.1 Grafiek van de normaalverdeling .................................................................................. 109
5.1.2.2 Interpretatie van standaarddeviatie ............................................................................... 109
5.2 Populatie............................................................................................................................. 110
5.9 Statistische test voor een populatiegemiddelde met een gekende variantie ........................ 110
,R Module .................................................................................................................................. 118
5.17 Toetsen van Hypothese voor onderzoek ........................................................................... 120
5.17.1 One Sample t-Test ......................................................................................................... 120
5.17.1.2 Analyse gebaseerd op kritieke waarden ...................................................................... 120
5.17.1.3 Analyse gebaseerd op p-waarden ............................................................................... 123
5.17.1.5 Alternatieven ............................................................................................................... 124
5.17.2 Skewness & Kurtosis tests ............................................................................................. 125
5.17.2.1.1 D’Agostino skewness test ........................................................................................ 125
5.17.5.1.2 Kurtosis test ............................................................................................................. 125
5.17.2.4 Alternatieven ............................................................................................................... 127
5.17.3 Gepaarde Two Sample t-Test ........................................................................................ 127
5.17.5 Unpaired Two Sample t-Test.......................................................................................... 129
5.17.5.1 Hypotheses - examples............................................................................................... 129
5.17.5.2 Analyse gebaseerd op p-waarden ............................................................................... 130
5.17.5.3 Assumpties ................................................................................................................. 132
5.17.5.4 Alternatieven ............................................................................................................... 132
15.7.6 Unpaired Two Sample Welch Test ................................................................................. 133
15.7.6.2 Analyse op basis van p-waarden ................................................................................ 133
5.17.7 Mann-Whitney U test ..................................................................................................... 133
5.17.7.1 Classical model ........................................................................................................... 134
5.17.7.1.2 Randomization model .............................................................................................. 134
5.17.7.2 Analyse op basis van p-waarden ................................................................................ 134
5.17.8 Bayesian Two Sample Test ........................................................................................... 135
5.17.9 Mediaan Test op basis van Notched Boxplots ................................................................ 135
5.17.10 Chi-kwadraat test for Count Data ................................................................................. 135
5.17.10.1 Pearson Chi-Kwadraat Test ...................................................................................... 135
5.17.10.1.4 Analyse gebaseerd op p-waarden – Output ........................................................... 136
5.17.10.1.5 Assumptie .............................................................................................................. 137
5.17.10.2 Exacte Pearson Chi-kwadraat Test met simulatie. .................................................... 137
5.17.11 One way analysis of Variance (1-way ANOVA) ............................................................ 138
5.17.11.2 Analyse gebaseerd op p-waarden ............................................................................. 138
5.17.12 Two Way Analysis of Variance (2-way ANOVA) ........................................................... 142
5.17.12.1 Analyse gebaseerd op p-waarden ............................................................................. 142
, 5.17.13 Testing Correlations ..................................................................................................... 147
5.17.14 Nota bij causaliteit ........................................................................................................ 147
HOOFDSTUK 6: Regressie modellen .......................................................................................... 149
6.1 Enkelvoudige lineair regressie model (Simple Lineair Regression Model: SLRM) ............... 149
6.1.2 Kleinste kwadratencriterium (Least Squares Criterion) ..................................................... 149
6.1.3 Ordinary Least Squares for Simple Linear Regression ..................................................... 150
6.1.4 Assumpties om regressiemodel op te stellen ................................................................... 151
6.1.5 Statistische eigenschappen van 𝛼 en 𝛽 ........................................................................... 151
6.1.5.2 Betrouwbaarheidsintervallen van eenvoudige lineaire regressieparameters ................. 153
6.2 Meervoudig lineair regressiemodel (Multiple Linear Regression Model: MLRM) ................. 154
6.2.1.3 Unbiasedness of b ........................................................................................................ 157
6.2.1.4 Minimum variantie (Gauss-Markov Theorema) ............................................................. 157
6.2.1.7 Determinatie coëfficiënt R² ............................................................................................ 158
6.2.1.8 Relatie tussen het SLRM en het MLRM ........................................................................ 158
6.2.2 Maximum Likelihood Estimation for Multiple Linear Regression ....................................... 159
Zelf regressiemodel maken met behulp van Excel en RFC ....................................................... 169
RFC: Multiple Regression (volledig uitgelegd) .......................................................................... 175
HOOFDSTUK 7: Introductie tot tijdreeksanalyse .......................................................................... 193
7.2 Case: the Market of Health and Personal Care Products .................................................... 193
7.3. Decompositie van tijdsreeksen .......................................................................................... 193
7.3.1. Klassieke decompositie van tijdsreeksen met “moving averages” ................................... 193
7.3.2 Seizoenale decompositie volgens Loess.......................................................................... 196
7.3.3. Decompositie volgens structurele tijdreeksmodellen. ...................................................... 197
7.4 Ad hoc forecasting van tijdreeksen ..................................................................................... 199
7.4.1 Regressieanalyse van tijdreeksen.................................................................................... 199
7.4.2 Smoothing Models ........................................................................................................... 203
7.4.2.4 Single Exponential Smoothing ...................................................................................... 203
7.4.2.5 Double Exponential Smoothing ..................................................................................... 204
7.4.2.6 Triple Exponential Smoothing (Holt-Winters model) ...................................................... 205
HOOFDSTUK 8: Univariate Box-Jenkins analyse ........................................................................ 211
8.2 Data .................................................................................................................................... 211
8.3 Theoretical Concepts .......................................................................................................... 212
8.3.0.1 Stationair Processes ..................................................................................................... 212
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