Quantitative Methods for Business Decisions 6e

Jon Curwin, University of Central England
Roger Slater, University of Central England
ISBN-13: 9781844805747
ISBN: 1844805743

[Purchase this ebook]

This is viewed as the clearest, most accurate and comprehensive book available in the field of quantitative methods. Now in line with the latest Excel developments, the book should cover the syllabus for a quantitative methods course on a business related degree course, and serve as a core text for professional examinations, and MBA courses.This comprehensive text, now in its fifth edition, teaches the reader how to apply the most widely used statistical methods in business. The book gives you the how, what, where, when and why of numbers and statistics. The book has twenty-five chapters divided into seven study areas. Each chapter focuses on a selection of techniques, illustrated with examples from business, marketing, economics, accounting, finance, and public administration.

Chapter Abstracts

• Ch. 1 The Quantitative Approach  [Purchase this echapter]
  Chapter One contrasts quantitative and qualitative approaches; how to identify some of the key elements of problem solving; how to understand the importance of methodology; how to appreciate the use of models; how to distinguish between data and information; how to identify different types of data; how to understand the importance of the level of measurement achieved and how to appreciate the importance of quantitative methods in business decision-making.
• Ch. 2 Managing Data  [Purchase this echapter]
  Chapter Two covers issues in managing data: data collection including the five W's and H technique and the definition of population and census; published sources and internet sources of data; the key differences between a census and sample including how we should decide sample size; and market research.
• Ch. 3 Survey Methods  [Purchase this echapter]
  Chapter Three covers survey methods: probability sampling including random sampling, stratification, cluster sampling and multi-stage designs; non-probability sampling including quota sampling, judgmental sampling, snowball sampling and convenience sampling; survey design including interviewer administered questionnaires or checklists, self-administered and miscellaneous methods; questionnaire design including question structure, question coding and question wording; and non-response, unsuitable for interview, those who have moved, those out at the time of call, those away for the period of the survey and those who refuse to co-operate.
• Ch. 4 Presentation of Data  [Purchase this echapter]
  Chapter Four covers the presentation of data including: raw data; tabulation of data; visual presentation including the use of percentages, the presentation of discrete data, pie charts and pictograms; presentation of continuous data including histograms; and graphical representation including plotting against time, actual and percentage increases, plotting a relationship and the Lorenz curve.
• Ch. 5 Measures of Location  [Purchase this echapter]
  Chapter Five covers measures of location: the mean, median and mode including untabulated data, the mean, the median, the mode, tabulated (ungrouped) discrete data, the mean, the median, the mode, tabulated (grouped) continuous data, the mean, the median, the median - the graphical method, the median - by calculation, the mode, the graphical method and the mode by calculation; and other measures of location including the geometric mean, the harmonic mean and weighted means.
• Ch. 6 Measures of Dispersion  [Purchase this echapter]
  Chapter Six covers measures of dispersion: the standard deviation including untabulated data, tabulated discrete data, tabulated (grouped) data and the variance; other measures of dispersion including the range, the quartile deviation, the graphical method, calculation of the quartiles, percentiles and back to raw data; relative measures of dispersion including coefficient of variation and coefficient of skewness; and variability in sample data.
• Ch. 7 Index Numbers  [Purchase this echapter]
  Chapter Seven covers index numbers: the interpretation of an index number including percentage changes, changing the base year and nominal and real change; the construction of index numbers, the simple price index, the simple aggregate price index, the average price relatives index, the Laspeyre index, the Paasche index and other indices; the weighting of index numbers; and the Retail Prices Index.
• Ch. 8 Probability  [Purchase this echapter]
  Chapter Eight covers probability: basic concepts; definitions including the 'classical' definition, the frequency definition, the subjective definition and the 'axiomatic' definition; basic relationships in probability; mutually exclusive events, non-mutually exclusive events; independent events and non-independent events; probability trees including independent events and dependent events; expected values; decision trees; Bayes' theorem; and Markov chains.
• Ch. 9 Discrete Probability Distributions  [Purchase this echapter]
  Chapter Nine covers discrete probability distributions including: uniform distribution; binomial distribution; Poisson distribution; and Poisson approximation to the binomial.
• Ch. 10 The Normal Distribution  [Purchase this echapter]
  Chapter Ten covers the Normal distribution: characteristics of the Normal distribution; the standard Normal distribution including area in a tail, area between two Z values and symmetry; combinations of variables; central limit theorem including generalization and proportions; Normal approximations including Normal approximation to the binomial and Normal approximation to the Poisson.
• Ch. 11 Confidence Intervals  [Purchase this echapter]
  Chapter Eleven covers the confidence intervals: statistical inference; inference about a population; confidence interval for the population mean including confidence intervals using survey data and sample size for a mean; confidence interval for a population percentage including sample size for a percentage; the difference between independent samples including confidence interval for the difference of means and confidence interval for the difference of percentages; the finite population correction factor; the t-distribution; and confidence interval for the median - large sample approximation.
• Ch. 12 Significance Testing  [Purchase this echapter]
  Chapter Twelve covers significance testing: significance testing using confidence intervals; hypothesis testing for single samples including a test statistic for a population mean and population percentage; one-sided significance tests including a one-sided test for a population mean, a one-sided test for a population percentage, a one-sided test for a population mean and producers' risk and consumers' risk; types of error including background theory; hypothesis testing with two samples including tests for a difference of means, tests for a difference in population percentage; hypothesis testing with small samples including single samples, two samples and matched pairs.
• Ch. 13 Non-parametric Tests  [Purchase this echapter]
  Chapter Thirteen covers non-parametric tests: chi-squared tests including tests of association, degrees of freedom, calculating the expected values, an adjustment, tests of goodness-of-fit, test for a uniform distribution, tests for binomial and Poisson distributions and test for the Normal distribution; Mann-Whitney U test including small sample test and large sample test; Wilcoxon test including small sample test and large sample test; and runs test.
• Ch. 14 Correlation  [Purchase this echapter]
  Chapter Fourteen covers correlation: scatter diagrams; cause and effect relationships; measuring linear association including rank correlation and correlation for cardinal data; the coefficient of determination; measuring non-linear association; and testing the significance of the correlation.
• Ch. 15 Regression  [Purchase this echapter]
  Chapter Fifteen covers regression: linear regression; the graph of the regression line; predictions from the regression line; another regression line; interpretation; and non-linear relationships.
• Ch. 16 Multiple Regression and Correlation  [Purchase this echapter]
  Chapter Sixteen covers multiple regression and correlation: the basic two variable model; the effects of adding variables; assumptions and econometric problems including multicollinearity, autocorrelation, lack of data, time and cost constraints, heteroskedasticity, under-identification and specification; analysis of a multiple regression model including multicollinearity, autocorrelation, lack of data, time and cost, under-identification and specification; and using multiple regression models.
• Ch. 17 Time Series  [Purchase this echapter]
  Chapter Seventeen covers time series: time series models including the factors, the additive model and the multiplicative model; the trend including trend by eye, a moving average trend and a linear regression trend; the seasonal factors including using an additive model, using a multiplicative model and seasonal adjustment of time series; the cyclical factors; the residual or random factor; predictions; developing models for short-term forecasts including measures of error, the naïve forecast, a simple average forecast; and exponentially weighted moving averages.
• Ch. 18 Mathematical Background  [Purchase this echapter]
  Chapter Eighteen covers mathematical background: basic arithmetic; basic algebra; use of powers; arithmetic and geometric progressions including arithmetic progression; functions including constant functions, linear functions, quadratic functions, cubic and polynomial functions and exponential functions.
• Ch. 19 The Time Value of Money  [Purchase this echapter]
  Chapter Nineteen covers the time value of money: interest - simple and compound including simple interest, compound interest and the use of present value tables; depreciation; present value including practical problems; the internal rate of return including the internal rate of return by graphical method, the internal rate of return by linear interpolation; incremental payments including sinking funds, annuities and mortgages; and annual percentage rate (APR).
• Ch. 20 Linear Programming  [Purchase this echapter]
  Chapter Twenty covers linear programming: definition of a feasible area; the solution of a linear programming problem including the maximization problem and the minimization problem; special cases including no feasible solution and multiple optimum solutions; the value of resources; computer-based solutions including formulating and solving problems with three or more products and using shadow price to evaluate new products.
• Ch. 21 Networks  [Purchase this echapter]
  Chapter Twenty-one covers networks: notation and construction; the critical path including the earliest start time, the latest start times, the critical path and total float; measures of float including free float and independent float; Gantt charts and managing resources; project time reduction; and uncertainty.
• Ch. 22 Modelling Stock Control and Queues  [Purchase this echapter]
  Chapter Twenty-two covers modelling stock control and queues: introduction to the economic order quantity model; quantity discounts; non-zero lead time including non-zero lead time and constant demand and non-zero lead time and probabilistic demand; introduction to modelling queues; a model for a single queue; queues - modelling cost; and modelling multi-channel queues.
• Ch. 23 Simulation  [Purchase this echapter]
  Chapter Twenty-three covers simulation: an introduction to simulation models; developing a simple simulation model; random event generation; the construction of a simulation model; and building a simulation model using a spreadsheet.
• Ch. 24 Game Theory  [Purchase this echapter]
  Chapter Twenty-four covers game theory: the structure of the game, the two-person zero-sum game including pure strategy games, mixed-strategy games; dominance; and solving larger problems.