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BL
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| Record Number
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891884
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| Main Entry
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Davis, Glyn.
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| Title & Author
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Business statistics using Excel /\ Glyn Davis Branko Pecar.
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| Edition Statement
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Second edition.
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| Publication Statement
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Oxford, United Kingdom :: Oxford University Press,, [2013]
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| Page. NO
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xvii, 486 pages ;; 25 cm
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| ISBN
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0199659516
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: 9780199659517
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Machine generated contents note: 1.Visualizing and presenting data -- Overview -- Learning objectives -- 1.1.The different types of data variable -- 1.2.Tables -- 1.2.1.What a table looks like -- 1.2.2.Creating a frequency distribution -- 1.2.3.Types of data -- 1.2.4.Creating a table using Excel PivotTable -- 1.2.5.Principles of table construction -- 1.3.Graphical representation of data -- 1.3.1.Bar charts -- 1.3.2.Pie charts -- 1.3.3.Histograms -- 1.3.4.Histograms with unequal class intervals -- 1.3.5.Frequency polygon -- 1.3.6.Scatter and time series plots -- 1.3.7.Superimposing two sets of data onto one graph -- Techniques in practice -- Summary -- Key terms -- Further reading -- 2.Data descriptors -- Overview -- Learning objectives -- 2.1.Measures of central tendency -- 2.1.1.Mean, median, and mode -- 2.1.2.Percentiles and quartiles -- 2.1.3.Averages from frequency distributions -- 2.1.4.Weighted averages -- 2.2.Measures of dispersion -- 2.2.1.The range
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Note continued: 2.2.2.The interquartile range and semi-interquartile range (SIQR) -- 2.2.3.The standard deviation and variance -- 2.2.4.The coefficient of variation -- 2.2.5.Measures of skewness and kurtosis -- 2.3.Exploratory data analysis -- 2.3.1.Five-number summary -- 2.3.2.Box plots -- 2.3.3.Using the Excel ToolPak add-in -- Techniques in practice -- Summary -- Key terms -- Further reading -- 3.Introduction to probability -- Overview -- Learning objectives -- 3.1.Basic ideas -- 3.2.Relative frequency -- 3.3.Sample space -- 3.4.The probability laws -- 3.5.The general addition law -- 3.6.Conditional probability -- 3.7.Statistical independence -- 3.8.Probability tree diagrams -- 3.9.Introduction to probability distributions -- 3.10.Expectation and variance for a probability distribution -- Techniques in practice -- Summary -- Key terms -- Further reading -- 4.Probability distributions -- Overview -- Learning objectives -- 4.1.Continuous probability distributions
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Note continued: 4.1.1.Introduction -- 4.1.2.The normal distribution -- 4.1.3.The standard normal distribution (Z distribution) -- 4.1.4.Checking for normality -- 4.1.5.Other continuous probability distributions -- 4.1.6.Probability density function and cumulative distribution function -- 4.2.Discrete probability distributions -- 4.2.1.Introduction -- 4.2.2.Binomial probability distribution -- 4.2.3.Poisson probability distribution -- 4.2.4.Poisson approximation to the binomial distribution -- 4.2.5.Normal approximation to the binomial distribution -- 4.2.6.Normal approximation to the Poisson distribution -- 4.2.7.Other discrete probability distributions -- Techniques in practice -- Summary -- Key terms -- Further reading -- 5.Sampling distributions and estimating -- Overview -- Learning objectives -- 5.1.Introduction to the concept of a sample -- 5.1.1.Why sample? -- 5.1.2.Sampling terminology -- 5.1.3.Types of samples -- 5.1.4.Types of error
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Note continued: 6.5.Two sample z-test for the population proportion -- 6.6.Two sample t-test for population mean (independent samples, equal variances) -- 6.7.Two sample tests for population mean (independent samples, unequal variances) -- 6.7.1.Two sample tests for independent samples (unequal variances) -- 6.7.2.Equivalent non-parametric test: Mann-Whitney U test -- 6.8.Two sample tests for population mean (dependent or paired samples) -- 6.8.1.Two sample tests for dependent samples -- 6.8.2.Equivalent non-parametric test: Wilcoxon matched pairs test -- 6.9.F test for two population variances (variance ratio test) -- 6.10.Calculating the size of the type II error and the statistical power -- Techniques in practice -- Summary -- Key terms -- Further reading -- 7.Chi-square and non-parametric hypothesis testing -- Overview -- Learning objectives -- 7.1.Chi-square tests -- 7.1.1.Chi-square test of association -- 7.1.2.Chi-square test for independent samples
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Note continued: 7.1.3.McNemar's test for matched (or dependent) pairs -- 7.1.4.Chi-square goodness-of-fit test -- 7.2.Non-parametric (or distribution-free) tests -- 7.2.1.Sign test -- 7.2.2.Wilcoxon signed rank sum test for dependent samples (or matched pairs) -- 7.2.3.Mann-Whitney U test for two independent samples -- Techniques in practice -- Summary -- Key terms -- Further reading -- 8.Linear correlation and regression analysis -- Overview -- Learning objectives -- 8.1.Linear correlation analysis -- 8.1.1.Scatter plots -- 8.1.2.Covariance -- 8.1.3.Pearson's correlation coefficient, r -- 8.1.4.Testing the significance of linear correlation between the two variables -- 8.1.5.Spearman's rank correlation coefficient -- 8.1.6.Testing the significance of Spearman's rank correlation coefficient, rs -- 8.2.Linear regression analysis -- 8.2.1.Construct scatter plot to identify model -- 8.2.2.Fit line to sample data -- 8.2.3.Sum of squares defined
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Note continued: 9.2.2.Aggregate indices -- 9.2.3.Deflating values -- 9.3.Trend extrapolation -- 9.3.1.A trend component -- 9.3.2.Fitting a trend to a time series -- 9.3.3.Types of trends -- 9.3.4.Using a trend chart function to forecast time series -- 9.3.5.Trend parameters and calculations -- 9.4.Moving averages and time series smoothing -- 9.4.1.Forecasting with moving averages -- 9.4.2.Exponential smoothing concept -- 9.4.3.Forecasting with exponential smoothing -- 9.5.Forecasting seasonal series with exponential smoothing -- 9.6.Forecasting errors -- 9.6.1.Error measurement -- 9.6.2.Types of errors -- 9.6.3.Interpreting errors -- 9.6.4.Error inspection -- 9.7.Confidence intervals -- 9.7.1.Population and sample standard errors -- 9.7.2.Standard errors in time series -- Techniques in practice -- Summary -- Key terms -- Further reading.
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| Abstract
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Business Statistics using Excel offers a comprehensive introduction to the subject of statistics and equips students with the tools and skills that will enable them to approach their course with confidence. The step-by-step methods are accompanied by illustrative Excel screenshots to provide clear and helpful explanations of the techniques you will need when applying Excel skills to business statistics. The text is designed for a typical one semester business statistics course and each chapter is packed with exercises to engage students and encourage self-assessment. This second edition has been fully revised to include an online refresher course in numerical skills and Microsoft Excel to reinforce students' confidence in their mathematical ability, or to check for basic maths knowledge if it has been some time since they studied it. The table of contents has been revised to more accurately map to a typical one semester Business Statistics course. More focus has been given to employability skills and the authors draw parallels between textbook content and employability skills, enabling students to contextualise their learning and identify how these skills can be applied and valued in real business environments. A wealth of pedagogical features have been integrated to ensure plenty of examples are used throughout as well as running 'techniques in practice' exercises at the end of each chapter.
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| Subject
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Business-- Computer programs.
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Commercial statistics-- Computer programs.
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Commercial statistics.
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Analyse des données.
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Bureautique.
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Business-- Computer programs.
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Commercial statistics-- Computer programs.
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Commercial statistics.
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Informatique.
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Logiciels.
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Manuels.
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Mathematics.
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| Subject
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Mathematics.
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Méthodes statistiques.
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| Subject
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Microsoft Excel (Computer file)
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Microsoft Excel (Computer file)
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| Dewey Classification
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005.54
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| LC Classification
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HF5548.4.M523D38 2013
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| Added Entry
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Pecar, Branko,1953-
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