Quantitative Methods for Business & Management

Description

Quantitative Methods for Business and Management Studentstakes you on a journey though the techniques required to succeed in business and management. With a user-friend accessible writing style, John Buglear presents these techniques simply and provides numerous examples to enable you to relate the theory to real-life applications. Cover Quantitative Methods for Business and Management Contents List of self-assembly guides Introduction: the Quantitative Methods road map Guided tour Acknowledgements Rules of the road – the basic techniques Introduction Quantitative methods, numbers and business What’s in this book? Key arithmetical procedures Review questions Straight ahead – linear models Reality check : Business use of break-even analysis and linear programming Introduction Linear equations Simultaneous equations Break-even analysis Inequalities Linear programming Review questions Around the bend – dealing with the curves Reality check: Business use of the EOQ model Introduction Simple forms of non-linear equations Basic differential calculus The Economic Order Quantity (EOQ) model Review questions Filling up – fuelling quantitative analysis Reality check: Business use of tabulation Introduction Important statistical terms Sources of data Types of data Arranging data Review questions Good visibility – pictorial presentation of data Reality check: Business use of pictorial presentation Introduction Displaying qualitative data Displaying quantitative data Portraying bivariate quantitative data Portraying time series data Review questions General directions – summarising data Reality check: Business use of summary measures Introduction Measures of location Measures of spread Summary measures in quality management Review questions Two-way traffic – investigating relationships between two variables using correlation and regression Reality check: Business use of quantitative bivariate analysis Introduction Correlation Simple linear regression Review questions Counting the cost – summarising money variables over time Reality check: Business use of price indices and investment appraisal Introduction Index numbers Review questions Long distance – analysing time series data Reality check: Business use of time series analysis and forecasting Introduction Components of time series Classical decomposition of time series data Exponential smoothing of time series data Review questions Is it worth the risk? – introducing probability Reality check: Business use of probability Introduction Measuring probability The types of probability The rules of probability Tree diagrams Review questions Finding the right way – analysing decisions Reality check: Business use of decision analysis Introduction Expectation Decision rules Review questions Accidents and incidence – discrete probability distributions and simulation Reality check: Business use of discrete probability distributions and simulation Introduction Simple probability distributions The binomial distribution The Poisson distribution Simulating business processes Review questions Smooth running – continuous probability distributions and basic queuing theory Reality check: Business use of the normal distribution Introduction The normal distribution The standard normal distribution The exponential distribution A simple queuing model Review questions Getting from A to B – project planning using networks Reality check: Business use of critical path analysis and PERT Introduction Network analysis Critical path analysis The programme evaluation and review technique (PERT) Cost analysis: crashing the project duration Review questions Taking short cuts – sampling methods Reality check: Business use of sampling Introduction Bias in sampling Probabilistic sampling methods Non-probabilistic sampling methods Test driving – sampling theory, estimation and hypothesis testing Reality check: Business use of small sample inference, the origins of the t distribution and testingpopulation proportions Introduction Sampling distributions Statistical inference: estimation Statistical inference: hypothesis testing Review questions High performance – statistical inferencefor comparing population means andbivariate data Reality check: Business use of contingency analysis and ANOVA Introduction Testing hypotheses about two population means Testing hypotheses about more thantwo population means – one-way ANOVA Testing hypotheses and producing interval estimatesfor quantitative bivariate data Contingency analysis Review questions Going off-road – managing quantitative research for projects and dissertations Introduction Using secondary data Collecting primary data Presenting your analysis Statistical and accounting tables Present values Binomial probabilities and cumulative binomial probabilities Poisson probabilities and cumulative Poisson probabilities Random numbers Cumulative probabilities for the standard normal distribution Selected points of the t distribution Selected points of the F distribution Selected points of the chi-square distribution Answers to review questions Index