Quantitative methods for management: a practical approach
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2019]
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xiii, 144 Seiten Diagramme |
| ISBN: | 9783030175535 9783030175566 |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents Part I Basics 1 Summary Statistics................................................................................... 1.1 Summary Statistics.......................................................................... 1.2 The Mean.......................................................................................... 1.3 Median and Percentiles................................................................... 1.4 The Standard Deviation................................................................... 1.5 Excel Functions.............................................................................. 1.6 The Histogram................................................................................. 1.7 The Normal Distribution................................................................. 1.8 Example: Tata Daily Returns.......................................................... 1.8.1 Presentation........................................................................ 1.8.2 Plotting the Data.............................................................. 1.8.3 Statistics............................................................................ 1.8.4 The 95% Interval............................................................... 1.9 Useful Tips ..................................................................................... 3 3 4 4 5 5 6 6 7 7 7 9 10 11 2 Probability Distributions.......................................................................... 2.1 Probability........................................................................................ 2.2
Probability Distributions................................................................. 2.3 Continuous Probability Distributions............................................ 2.4 The Normal Distribution................................................................. 2.5 Transformations............................................................................... 2.6 Time Series Data............................................................................ 2.7 Example: The EuroLeague Final Four.......................................... 2.7.1 Presentation........................................................................ 2.7.2 The Data............................................................................ 2.7.3 Raw Data Analysis............................................................ 2.7.4 Aggregate Data Analysis ................................................. 2.7.5 Fogarithmic Transformation............................................ 2.8 Useful Tips ...................................................................................... 13 13 14 15 16 18 18 19 19 20 20 21 23 24 IX
x Contents Part II Regression Analysis 3 The Regression Line................................................................................. 3.1 A Trivial Example.......................................................................... 3.2 Simple Linear Regression............................................................... 3.3 Predicted Values and Residuals..................................................... 3.4 Interpretating the Regression Coefficients..................................... 3.5 Correlation........................................................................................ 3.6 Obtaining the Regression Line in Excel....................................... 3.7 Example: Predicting Sales from Price............................................ 3.7.1 Presentation........................................................................ 3.7.2 The Data............................................................................ 3.7.3 Regression Line................................................................. 3.7.4 Predictive Model............................................................... 3.8 Useful Tips ..................................................................................... 27 27 29 29 30 30 31 31 31 32 32 34 35 4 Multiple Regression................................................................................... 4.1 Multiple Linear Regression............................................................ 4.2 Predicted Values and Residuals..................................................... 4.3 Interpreting the Regression
Coefficients....................................... 4.4 Multiple Correlation........................................................................ 4.5 Obtaining a Regression Equation in Excel................................... 4.6 Example: Concrete Quality Control.............................................. 4.6.1 Presentation........................................................................ 4.6.2 The Data............................................................................ 4.6.3 Regression Line(1)........................................................... 4.6.4 Regression Line(2)........................................................... 4.6.5 Regression Line(3)........................................................... 4.6.6 Multiple Regression Analysis.......................................... 4.7 Useful Tips ..................................................................................... 37 37 38 38 39 39 41 41 41 42 42 43 43 45 5 Testing Regression Coefficients............................................................... 5.1 Statistical Inference.......................................................................... 5.2 Confidence Limits............................................................................ 5.3 Significance...................................................................................... 5.4 The p-Values................................................................................... 5.5 Multicollinearity............................................................................... 5.6 Example: Orange Juice
Pricing..................................................... 5.6.1 Presentation........................................................................ 5.6.2 The Data............................................................................ 5.6.3 How Does Minute Maid’sPrice Affect Its Market Share?................................................................................. 5.6.4 Correlation Analysis.......................................................... 5.6.5 Another Regression Analysis .......................................... 47 47 48 49 50 50 51 51 52 52 53 53
Contents xi 5.6.6 5.6.7 What Is theImpact of Minute Maid’s Price?.................. What Will Happen if Minute Maid Does Not React to Tropicana’s Move?............................................ Useful Tips ...................................................................................... 54 Dummy Variables..................................................................................... 6.1 Dummy Variables............................................................................ 6.2 Coding Two Groups with a Dummy............................................ 6.3 Three Groups................................................................................... 6.4 Clarification...................................................................................... 6.5 Any Number ofGroups .................................................................. 6.6 Example: Gender Salary Gap.......................................................... 6.6.1 Presentation........................................................................ 6.6.2 The Data............................................................................ 6.6.3 How Wide Is the Gender Salary Gap?............................ 6.6.4 Can the Gap Be Explained by the Number of Years with the Company?............................................ 6.6.5 Regression Analysis (1).................................................... 6.6.6 Regression Analysis (2).................................................... 6.7 Useful Tips ..................................................................................... 57 57 57
58 59 59 60 60 60 61 Interaction ................................................................................................. 7.1 Interaction in a Regression Equation............................................ 7.2 Interpretation of an Interaction Term............................................ 7.3 Example: Diesel Consumption....................................................... 7.3.1 Presentation........................................................................ 7.3.2 The Data............................................................................ 7.3.3 Regression Line (1).......................................................... 7.3.4 Regression Line (2).......................................................... 7.3.5 Multiple Regression Analysis.......................................... 7.3.6 Splitting the Sample by Motor Type.............................. 7.3.7 Analysis with Interaction Terms..................................... 7.4 Useful Tips ..................................................................................... 65 65 66 66 66 67 67 67 69 69 70 71 5.7 6 7 Part III 8 54 55 61 62 62 63 Classification Classification Models................................................................................. 8.1 Classification Models..................................................................... 8.2 Binary Classification........................................................................ 8.3 Confusion Matrix............................................................................ 8.4 Example: Default at Alexia
Bank................................................... 8.4.1 Presentation........................................................................ 8.4.2 The Data Set..................................................................... 8.4.3 Data Description .............................................................. 75 75 76 77 78 78 78 78
xii Contents 8.4.4 Regression Analysis.......................................................... 8.4.5 Classification...................................................................... Useful Tips ..................................................................................... 79 79 82 Out-of-Sample Validation........................................................................ 9.1 Overfitting........................................................................................ 9.2 Out-of-Sample Validation............................................................... 9.3 Example: The Chum Model.......................................................... 9.3.1 Presentation........................................................................ 9.3.2 The Data Set...................................................................... 9.3.3 Dropping Redundant Information................................... 9.3.4 Splitting the Data Set........................................................ 9.3.5 Regression Equation.......................................................... 9.3.6 Evaluation in the Training Set.......................................... 9.3.7 Evaluation in the Test Set................................................. 9.4 Useful Tips ...................................................................................... 83 83 83 84 84 84 85 86 86 87 88 89 8.5 9 Part IV Time Series Data 10 Trend and Seasonality ............................................................................. 10.1 Time Series
Data............................................................................. 10.2 Trends............................................................................................... 10.3 Seasonality........................................................................................ 10.4 Forecasting........................................................................................ 10.5 Prediction Error............................................................................... 10.6 Example: Polar Bear Sales............................................................. 10.6.1 Presentation........................................................................ 10.6.2 Estimating the Trend........................................................ 10.6.3 Seasonality.......................................................................... 10.6.4 Prediction Error................................................................. 10.6.5 Forecasting the Next Year Sales..................................... 10.7 Useful Tips ...................................................................................... 93 93 94 95 96 96 97 97 97 98 99 99 100 11 Nonlinear Trends...................................................................................... 11.1 Nonlinear Trends............................................................................. ! 1.2 Out-of-Sample Validation............................................................... 11.3 Example: The Bayou Beer Sales................................................... 11.3.1
Presentation........................................................................ 11.3.2 Estimating the Trend........................................................ 11.3.3 Seasonality.......................................................................... 11.3.4 Prediction Error................................................................. 11.3.5 Forecasting the Sales for theYear 2017........................... 11.4 Useful Tips ...................................................................................... 103 103 104 105 105 105 106 106 108 109
Contents x¡¡¡ 12 Moving Average Trends......................................................................... Ill 12.1 Nonparametric Trends.................................................................... Ill 12.2 Moving Average.............................................................................. 112 12.3 Exponential Smoothing.................................................................. 112 12.4 Deseasonalizing.............................................................................. 114 12.5 Example: Brandy Consumption in Australia................................ 114 12.5.1 Presentation....................................................................... 114 12.5.2 Parametric Trend Approach.............................................. 115 12.5.3 Moving Average Trend..................................................... 116 12.5.4 Seasonality......................................................................... 117 12.5.5 Deseasonalized Sales....................................................... 117 12.5.6 Exponential Smoothing..................................................... 118 12.6 Useful Tips ..................................................................................... 119 13 Holt-Winters Forecasting....................................................................... 121 13.1 Introduction..................................................................................... 121 13.2 The Holt-Winters Approach........................................................... 122 13.3 Multiplicative
Seasonals................................................................ 122 13.4 The First Year................................................................................ 123 13.5 Forecasting One Year Ahead......................................................... 123 13.6 Additive Seasonals......................................................................... 124 13.7 Example: Supermercados Andinos................................................ 124 13.7.1 Presentation....................................................................... 124 13.7.2 Initializing the Model....................................................... 125 13.7.3 Fitting the Model.............................................................. 125 13.7.4 Forecasting 6 Months Ahead............................................ 127 13.7.5 Alternative Model ........................................................... 127 13.8 Useful Tips ..................................................................................... 128 Appendix: R Code........................................................................................... 129
|
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| author | Canela, Miguel Ángel Alegre, Inés Ibarra, Alberto |
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| spelling | Canela, Miguel Ángel Verfasser (DE-588)1245899414 aut Quantitative methods for management a practical approach Miguel Ángel Canela, Inés Alegre, Alberto Ibarra Cham Springer [2019] © 2019 xiii, 144 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Quantitative Methode (DE-588)4232139-6 gnd rswk-swf Datenanalyse (DE-588)4123037-1 gnd rswk-swf Management (DE-588)4037278-9 gnd rswk-swf Management (DE-588)4037278-9 s Quantitative Methode (DE-588)4232139-6 s Datenanalyse (DE-588)4123037-1 s Regressionsanalyse (DE-588)4129903-6 s 1\p DE-604 Alegre, Inés Verfasser aut Ibarra, Alberto Verfasser aut Erscheint auch als Online-Ausgabe 10.1007/978-3-030-17554-2 978-3-030-17554-2 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031460815&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Canela, Miguel Ángel Alegre, Inés Ibarra, Alberto Quantitative methods for management a practical approach Regressionsanalyse (DE-588)4129903-6 gnd Quantitative Methode (DE-588)4232139-6 gnd Datenanalyse (DE-588)4123037-1 gnd Management (DE-588)4037278-9 gnd |
| subject_GND | (DE-588)4129903-6 (DE-588)4232139-6 (DE-588)4123037-1 (DE-588)4037278-9 |
| title | Quantitative methods for management a practical approach |
| title_auth | Quantitative methods for management a practical approach |
| title_exact_search | Quantitative methods for management a practical approach |
| title_full | Quantitative methods for management a practical approach Miguel Ángel Canela, Inés Alegre, Alberto Ibarra |
| title_fullStr | Quantitative methods for management a practical approach Miguel Ángel Canela, Inés Alegre, Alberto Ibarra |
| title_full_unstemmed | Quantitative methods for management a practical approach Miguel Ángel Canela, Inés Alegre, Alberto Ibarra |
| title_short | Quantitative methods for management |
| title_sort | quantitative methods for management a practical approach |
| title_sub | a practical approach |
| topic | Regressionsanalyse (DE-588)4129903-6 gnd Quantitative Methode (DE-588)4232139-6 gnd Datenanalyse (DE-588)4123037-1 gnd Management (DE-588)4037278-9 gnd |
| topic_facet | Regressionsanalyse Quantitative Methode Datenanalyse Management |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031460815&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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