Business statistics : a multimedia guide to concepts and applications / Moya McCloskey and Chris Robertson.
By: McCloskey, Moya
.
Contributor(s): Robertson, Chris
.
Material type:
BookPublisher: London : Arnold, 2000Description: xxiii, 385 p. ; 25 cm.ISBN: 0340719273; 9780340719275.Subject(s): Commercial statistics| Item type | Current library | Call number | Copy number | Status | Barcode | |
|---|---|---|---|---|---|---|
| General lending | MTU Kerry North Campus Library First Floor Main | 519.202456 ROB (Browse shelf(Opens below)) | 1 | Available | 38888000422760 |
Enhanced descriptions from Syndetics:
This book and CD pack is the first multimedia type product aimed at teaching basic statistics to business students. The CD provides computer based tutorials and customizable practical material. The book acts as a study guide, allowing the student to check previous learning. The software is Windows-based and generates tips and responses in response to the student's input.
CD-ROM in back pocket.
Includes index.
This is a CD-ROM/book package for teaching basic statistics to business students. The CD-ROM provides computer-based tutorials and practice material that can be customized and used by the student. The book acts as a study guide.
Table of contents provided by Syndetics
- List of figures (p. xi)
- List of tables (p. xvii)
- Preface (p. xxi)
- Acknowledgments (p. xxv)
- 1 Introduction (p. 1)
- 1.1 Opinion polls (p. 1)
- 1.2 Supermarket relocation (p. 3)
- 1.3 Financial indices (p. 5)
- 1.4 Official statistics (p. 7)
- 1.5 School and hospital league tables (p. 8)
- 1.6 Common features of statistical studies: what exactly is statistics? (p. 11)
- 1.7 Statistical techniques in business (p. 12)
- 2 Summarizing business surveys: populations and samples, variables and variability (p. 14)
- 2.1 Populations and samples (p. 14)
- 2.2 Types of variable (p. 17)
- 2.3 Location and variability in quantitative variables (p. 21)
- 2.4 Qualitative variables--proportions (p. 32)
- 3 Graphs for investigating distribution and relationships (p. 35)
- 3.1 Introduction (p. 35)
- 3.2 Histogram (p. 36)
- 3.3 Stem and leaf plot (p. 43)
- 3.4 Boxplot (p. 47)
- 3.5 Cumulative distribution function plot (p. 51)
- 3.6 Bar chart and pie chart (p. 53)
- 3.7 Scatter plot (p. 57)
- 3.8 Time series plot (p. 61)
- 3.9 Misleading displays (p. 63)
- 3.10 Summary (p. 66)
- 4 Index numbers (p. 68)
- 4.1 Introduction (p. 68)
- 4.2 Weighted averages (p. 70)
- 4.3 Simple index numbers (p. 73)
- 4.4 Weighted index numbers (p. 78)
- 4.5 Retail price index (p. 84)
- 5 Large surveys and market research surveys (p. 88)
- 5.1 Planning a survey (p. 88)
- 5.2 Sampling schemes (p. 93)
- 5.3 United Kingdom large government-sponsored surveys (p. 102)
- 5.4 Differences between major election opinion poll groups (p. 106)
- 5.5 Questionnaire designs (p. 109)
- 5.6 Bias and representative studies (p. 118)
- 5.7 Data presentation, tables and bar charts (p. 120)
- 6 Investigating relationships (p. 122)
- 6.1 Housing data--different types of associations (p. 123)
- 6.2 Common transformations to linearity (p. 125)
- 6.3 What is a relationship? (p. 126)
- 6.4 Correlation (p. 127)
- 6.5 Regression lines (p. 131)
- 6.6 Lorenz plot (p. 135)
- 6.7 Summary (p. 139)
- 7 Relationships with time (p. 140)
- 7.1 Introduction (p. 140)
- 7.2 Simple time series models (p. 141)
- 7.3 Moving averages (p. 143)
- 7.4 Exponential smoothing (p. 148)
- 7.5 Correcting for seasonality (p. 150)
- 7.6 Forecasting (p. 154)
- 7.7 Summary (p. 159)
- 8 Probability as a model for random events (p. 160)
- 8.1 Introduction (p. 160)
- 8.2 Events and samples spaces (p. 161)
- 8.3 Probabilities and their interpretation (p. 165)
- 8.4 Mutually exclusive and independent events (p. 172)
- 8.5 Addition law, multiplication law and complementary events (p. 177)
- 8.6 Bayes' theorem (p. 181)
- 8.7 Summary (p. 183)
- 9 Probability distributions as a model for populations (p. 184)
- 9.1 Key ideas on random variables, expectation and variability (p. 184)
- 9.2 Binomial distribution (p. 191)
- 9.3 Continuous models (p. 199)
- 9.4 Normal distribution (p. 200)
- 9.5 Summary (p. 207)
- 10 Sampling distributions (p. 209)
- 10.1 Introduction (p. 209)
- 10.2 Random samples, repeated samples and sampling distributions (p. 210)
- 10.3 Bias (p. 216)
- 10.4 Standard error (p. 218)
- 10.5 Central limit theorem (p. 219)
- 10.6 Sampling distribution of the sample mean (p. 221)
- 10.7 Sampling distribution of the sample proportion (p. 226)
- 10.8 Precision and accuracy (p. 232)
- 10.9 Sample size calculations for standard errors (p. 233)
- 11 Estimation and confidence intervals (p. 236)
- 11.1 Introduction (p. 236)
- 11.2 Confidence interval for the mean of a population (p. 239)
- 11.3 Confidence interval for a population proportion (p. 248)
- 11.4 Difference of means based on independent samples (p. 250)
- 11.5 Difference of two population proportions (p. 253)
- 11.6 Large and small samples (p. 256)
- 11.7 Sample size calculations for confidence interval width (p. 257)
- 12 Significance tests (p. 261)
- 12.1 Introducing tests and errors (p. 261)
- 12.2 Components of a significance test (p. 269)
- 12.3 One-sample t test for a mean (p. 274)
- 12.4 t test for the difference of two independent means (p. 282)
- 12.5 t test for paired differences (p. 289)
- 12.6 Testing proportions (p. 294)
- 12.7 General points on the interpretation of significance tests (p. 298)
- 12.8 Power and sample size calculations (p. 302)
- 13 Qualitative variables: goodness of fit and association (p. 308)
- 13.1 Goodness-of-fit tests (p. 308)
- 13.2 Goodness of fit of a simple discrete probability model (p. 309)
- 13.3 X[superscript 2] goodness-of-fit test (p. 313)
- 13.4 Association (p. 314)
- 13.5 X[superscript 2] independence test for 2 x 2 tables (p. 317)
- 13.6 X[superscript 2] independence test for r x c tables (p. 321)
- 13.7 Large residuals (p. 322)
- 13.8 Sample size (p. 323)
- 14 Correlation (p. 325)
- 14.1 Introduction (p. 325)
- 14.2 Estimate and confidence interval (p. 326)
- 14.3 Testing (p. 330)
- 14.4 Interpretation: causality and spurious correlations (p. 332)
- 14.5 Rank correlation (p. 335)
- 15 Linear regression (p. 338)
- 15.1 Introduction (p. 338)
- 15.2 Linear regression model (p. 341)
- 15.3 Relationship of the slope to the correlation coefficient (p. 345)
- 15.4 Confidence intervals for the estimates (p. 347)
- 15.5 Centring (p. 351)
- 15.6 Case study: capital asset pricing model (p. 353)
- 15.7 Residuals and outliers: checking the validity of the model (p. 356)
- 15.8 Confidence intervals for a predicted mean and predicted single value (p. 361)
- 15.9 Qualitative explanatory variables (p. 368)
- 15.10 More than one explanatory variable: multiple regression (p. 371)
- 15.11 Summary (p. 374)
- Appendix A Table of the standard normal distribution (p. 376)
- Appendix B Percentage points of the t distribution (p. 377)
- Appendix C Percentage points of the X[superscript 2] distribution (p. 378)
- References (p. 379)
- Index (p. 381)
Author notes provided by Syndetics
Chris Robertson is Professor of Public Epidemiology at the Department of Statistics and Modelling Science, Strathclyde UniversityMoya McCloskey is a former Lecturer in the Department of Statistics and Modelling Science, Strathclyde University