000 | a | ||
---|---|---|---|
999 |
_c30952 _d30952 |
||
008 | 220610b xxu||||| |||| 00| 0 eng d | ||
020 | _a9783030870225 | ||
082 |
_a658.4033 _bPAC |
||
100 | _aPaczkowski, Walter R. | ||
245 | _aBusiness analytics : data science for business problems | ||
260 |
_bSpringer, _c2021 _aCham : |
||
300 |
_axxxviii, 387 p. ; _bill., _c25 cm |
||
365 |
_b109.99 _cEUR _d86.00 |
||
504 | _aInclude bibliographic references and index. | ||
520 | _aThis book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research. | ||
650 | _aDecision making | ||
650 | _aMathematical models | ||
650 | _aStrategic planning | ||
650 | _aBusiness intelligence | ||
650 | _aAccuracy report | ||
650 | _a Autoregressive model(AR) | ||
650 | _aCross-sectional data | ||
650 | _aDecision trees | ||
650 | _aDisturbance term | ||
650 | _aElasticity | ||
650 | _aEconometrics | ||
650 | _aFit method | ||
650 | _a Frequency table | ||
650 | _a Gaussian distribution | ||
650 | _a Heatmap | ||
650 | _aHypothesis testing | ||
650 | _aK-means clustering | ||
650 | _a Label Encoding | ||
650 | _aMosaic graph | ||
650 | _aNaive Bayes | ||
650 | _a Outliers | ||
650 | _aPanel data set | ||
650 | _aStatsmodels | ||
650 | _aTraining data set | ||
650 | _aUnrestricted model | ||
650 | _aZ-transform | ||
650 | _aSpatial data | ||
650 | _aTime senses analysis | ||
942 |
_2ddc _cBK |