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Business Analytics Custom Book

by: Berenson

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On-line Price: $92.39 (includes GST)

Paperback package 0

23%Off Retail Price

You save: $28.00

TBA - ETA is is usually around 2 weeks.
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N.Sydney : On Order (reserve your copy)

Retail Price: $120.39

Publisher: PEARSON EDUCATION AU,04.03.13

Category: Business Information Systems Level: B/I/A

ISBN: 1486013767
ISBN13: 9781486013760

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CONTENTS PART 1 . PRESENTING AND DESCRIBING INFORMATION 1 | INTRODUCTION AND DATA COLLECTION 2 Introduction to Business Analytics 2 1.1 Basic concepts of statistics 8 1.2 The growth of statistics and information technology 10 1.3 Collecting data 11 1.4 Types of variables 13 Summary 16 Key terms 16 Chapter review problems 16 2 | PRESENTING DATA IN TABLES AND CHARTS 19 2.1 Tables and charts for categorical data 20 2.2 Organising numerical data 25 2.3 Tables and charts for numerical data 28 2.4 Cross-tabulations 37 2.5 Scatter diagrams and time-series plots 40 2.6 Misusing graphs and ethical issues 43 Summary 47 Key terms 47 Chapter review problems 48 3 | NUMERICAL DESCRIPTIVE MEASURES 51 3.1 Measures of central tendency, variation and shape 52 3.2 Numerical descriptive measures for a population 71 3.3 Calculating numerical descriptive measures from a frequency distribution 75 3.4 Five-number summary and box-and-whisker plots 78 3.5 Covariance and the coefficient of correlation 81 3.6 Statistical thinking in business decisions 87 3.7 Pitfalls in numerical descriptive measures and ethical issues 91 Summary 92 Key formulas 92 Key terms 94 Chapter review problems 94 PART 2 . MEASURING UNCERTAINTY 4 | BASIC PROBABILITY 100 4.1 Basic probability concepts 101 4.2 Conditional probability 109 4.3 Ethical issues and probability 115 Summary 116 Key formulas 117 Key terms 117 Chapter review problems 117 5 | SOME IMPORTANT DISCRETE PROBABILITY DISTRIBUTIONS 120 5.1 Probability distribution for a discrete random variable 121 5.2 Binomial distribution 125 5.3 Poisson distribution 132 Summary 136 Key formulas 136 Key terms 137 Chapter review problems 137 6 | THE NORMAL DISTRIBUTION (CONTINUOUS DISTRIBUTION) 140 6.1 Continuous probability distributions 141 6.2 The normal distribution 142 6.3 Evaluating normality 157 6.4 The normal approximation to the binomial distribution 160 Summary 163 Key formulas 163 Key terms 163 Chapter review problems 163 7 | SAMPLING DISTRIBUTIONS 165 7.1 Sampling distributions 166 7.2 Sampling distribution of the mean 166 7.3 Sampling distribution of the proportion 176 7.4 Types of survey sampling methods 179 7.5 Evaluating survey worthiness 184 Summary 188 Key formulas 189 Key terms 189 Chapter review problems 189 PART 3 . DRAWING CONCLUSIONS ABOUT POPULATIONS BASED ONLY ON SAMPLE INFORMATION 8 | CONFIDENCE INTERVAL ESTIMATION 194 8.1 Confidence interval estimation for the mean (s known) 195 8.2 Confidence interval estimation for the mean (s unknown) 200 8.3 Confidence interval estimation for the proportion 206 8.4 Determining sample size 209 8.5 Confidence interval estimation and ethical issues 215 Summary 216 Key formulas 216 Key terms 216 Chapter review problems 217 9 | FUNDAMENTALS OF HYPOTHESIS TESTING: ONE-SAMPLE TESTS 222 9.1 Hypothesis-testing methodology 223 9.2 Z test of hypothesis for the mean (s known) 229 9.3 One-tail tests 236 9.4 t test of hypothesis for the mean (s unknown) 241 9.5 Z test of hypothesis for the proportion 247 9.6 Potential hypothesis-testing pitfalls and ethical issues 251 Summary 254 Key formulas 255 Key terms 255 Chapter review problems 257 PART 4 . DETERMINING CAUSE AND MAKING RELIABLE FORECASTS 10 | SIMPLE LINEAR REGRESSION 260 10.1 Types of regression models 261 10.2 Determining the simple linear regression equation 263 10.3 Measures of variation 272 10.4 Assumptions 278 10.5 Residual analysis 278 10.6 Inferences about the slope and correlation coefficient 282 10.7 Estimation of mean values and prediction of individual values 289 10.8 Pitfalls in regression and ethical issues 293 Summary 296 Key formulas 297 Key terms 298 Chapter review problems 298 11 | TIME-SERIES FORECASTING AND INDEX NUMBERS 304 11.1 The importance of business forecasting 305 11.2 Component factors of the classical multiplicative time-series model 306 11.3 Smoothing the annual time series 307 11.4 Least-squares trend-fitting and forecasting 314 11.5 Choosing an appropriate forecasting model 326 11.6 Time-series forecasting of seasonal data 331 11.7 Index numbers 339 11.8 Pitfalls in time-series forecasting 346 Summary 347 Key formulas 348 Key terms 349 Chapter review problems 349 APPENDICES A Review of arithmetic 354 B Summation notation 356 C Statistical symbols and Greek alphabet 359 D Data sets and data tools overview 360 E Tables 361 Glossary 377 Index 384