Muutke küpsiste eelistusi

Business Statistics using Excel 2nd Revised edition [Pehme köide]

3.00/5 (7 hinnangut Goodreads-ist)
(Principal Lecturer in e-Business and Data Analysis, Teesside University Teaching Fellow), (Visiting Fellow of the University of Gloucestershire; VP- ExxonMobil Global Account, Emerson Process Management)
  • Formaat: Paperback / softback, 504 pages, kõrgus x laius x paksus: 247x189x22 mm, kaal: 940 g
  • Ilmumisaeg: 28-Feb-2013
  • Kirjastus: Oxford University Press
  • ISBN-10: 0199659516
  • ISBN-13: 9780199659517
Teised raamatud teemal:
Business Statistics using Excel 2nd Revised editionSuurem pilt
  • Formaat: Paperback / softback, 504 pages, kõrgus x laius x paksus: 247x189x22 mm, kaal: 940 g
  • Ilmumisaeg: 28-Feb-2013
  • Kirjastus: Oxford University Press
  • ISBN-10: 0199659516
  • ISBN-13: 9780199659517
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780199659517.html
Märksõnad:
Business Statistics using Excel offers a step-by-step guide to the theory and methodology behind the use of statistics in business. Integrated screenshots offer clear guidance through each Excel process and exercises are imbedded throughout each chapter to ensure that students engage with the content and frequently test their understanding.

Offering a comprehensive, "step-by-step" approach to the subject, Business Statistics Using Excel, Second Edition, gives students the tools and skills they need to succeed in their coursework.

FEATURES
- "Techniques in Practice" exercises at the end of each chapter encourage self-assessment
- Excel screenshots provide clear and helpful examples that illustrate how to apply Excel skills to business statistics
- Full integration of Excel exercises and applications--both in the textbook and on the Companion Website--enable both classroom-led learning or self-directed study

NEW TO THIS EDITION
- Expanded coverage of probability and probability distributions
- Updated checklists help students to link the skills to their own development portfolios
- All chapters have been fully revised and updated to include additional examples, explanations, and discussion questions
- Greater emphasis on employability skills, which enables students to contextualize their learning and also helps them to identify how these skills can be applied and valued in real business environments

The accompanying Companion Website offers a variety of features:

For students:
- Introduction to Microsoft Excel 2010
- Self-test multiple-choice questions
- Data from the exercises in the book
- Links to key websites
- Online glossary
- Revision tips
- Visual walk-throughs
- Numerical-skills workbook: New to the second edition, this online refresher course covering basic math and Microsoft Excel helps reinforce students' confidence in their mathematical ability

For instructors:
- Instructor's Manual containing a guide to structuring lectures and worked-out answers to exercises in the book
- PowerPoint slides
- A Testbank with thirty questions per chapter
How to use this book xiv
How to use the Online Resource Centre xvi
1 Visualizing and presenting data
1(57)
Overview
1(1)
Learning objectives
2(1)
1.1 The different types of data variable
2(1)
1.2 Tables
3(18)
1.2.1 What a table looks like
4(2)
1.2.2 Creating a frequency distribution
6(4)
1.2.3 Types of data
10(1)
1.2.4 Creating a table using Excel PivotTable
11(10)
1.2.5 Principles of table construction
21(1)
1.3 Graphical representation of data
21(37)
1.3.1 Bar charts
22(5)
1.3.2 Pie charts
27(4)
1.3.3 Histograms
31(9)
1.3.4 Histograms with unequal class intervals
40(2)
1.3.5 Frequency polygon
42(5)
1.3.6 Scatter and time series plots
47(4)
1.3.7 Superimposing two sets of data onto one graph
51(3)
Techniques in practice
54(2)
Summary
56(1)
Key terms
57(1)
Further reading
57(1)
2 Data descriptors
58(49)
Overview
58(1)
Learning objectives
59(1)
2.1 Measures of central tendency
59(21)
2.1.1 Mean, median, and mode
59(4)
2.1.2 Percentiles and quartiles
63(4)
2.1.3 Averages from frequency distributions
67(10)
2.1.4 Weighted averages
77(3)
2.2 Measures of dispersion
80(14)
2.2.1 The range
82(1)
2.2.2 The interquartile range and semi-interquartile range (SIQR)
82(1)
2.2.3 The standard deviation and variance
83(5)
2.2.4 The coefficient of variation
88(1)
2.2.5 Measures of skewness and kurtosis
89(5)
2.3 Exploratory data analysis
94(13)
2.3.1 Five-number summary
94(2)
2.3.2 Box plots
96(4)
2.3.3 Using the Excel ToolPak add-in
100(2)
Techniques in practice
102(2)
Summary
104(1)
Key terms
105(1)
Further reading
105(2)
3 Introduction to probability
107(28)
Overview
107(1)
Learning objectives
107(1)
3.1 Basic ideas
107(2)
3.2 Relative frequency
109(3)
3.3 Sample space
112(2)
3.4 The probability laws
114(1)
3.5 The general addition law
115(2)
3.6 Conditional probability
117(3)
3.7 Statistical independence
120(3)
3.8 Probability tree diagrams
123(1)
3.9 Introduction to probability distributions
124(3)
3.10 Expectation and variance for a probability distribution
127(8)
Techniques in practice
131(2)
Summary
133(1)
Key terms
133(1)
Further reading
133(2)
4 Probability distributions
135(50)
Overview
135(1)
Learning objectives
135(1)
4.1 Continuous probability distributions
136(19)
4.1.1 Introduction
136(1)
4.1.2 The normal distribution
136(4)
4.1.3 The standard normal distribution (Z distribution)
140(9)
4.1.4 Checking for normality
149(4)
4.1.5 Other continuous probability distributions
153(1)
4.1.6 Probability density function and cumulative distribution function
154(1)
4.2 Discrete probability distributions
155(30)
4.2.1 Introduction
155(1)
4.2.2 Binomial probability distribution
155(10)
4.2.3 Poisson probability distribution
165(8)
4.2.4 Poisson approximation to the binomial distribution
173(2)
4.2.5 Normal approximation to the binomial distribution
175(5)
4.2.6 Normal approximation to the Poisson distribution
180(2)
4.2.7 Other discrete probability distributions
182(1)
Techniques in practice
182(1)
Summary
183(1)
Key terms
183(1)
Further reading
184(1)
5 Sampling distributions and estimating
185(58)
Overview
185(1)
Learning objectives
185(1)
5.1 Introduction to the concept of a sample
186(7)
5.1.1 Why sample?
186(1)
5.1.2 Sampling terminology
187(1)
5.1.3 Types of samples
188(4)
5.1.4 Types of error
192(1)
5.2 Sampling from a population
193(24)
5.2.1 Introduction
193(1)
5.2.2 Population versus sample
194(1)
5.2.3 Sampling distributions
194(1)
5.2.4 Sampling distribution of the mean
194(4)
5.2.5 Sampling from a normal population
198(6)
5.2.6 Sampling from a non-normal population
204(6)
5.2.7 Sampling distribution of the proportion
210(2)
5.2.8 Using Excel to generate a sample from a sampling probability distribution
212(5)
5.3 Population point estimates
217(8)
5.3.1 Introduction
217(1)
5.3.2 Types of estimate
218(1)
5.3.3 Criteria of a good estimator
218(1)
5.3.4 Point estimate of the population mean and variance
218(4)
5.3.5 Point estimate for the population proportion and variance
222(2)
5.3.6 Pooled estimates
224(1)
5.4 Population confidence intervals
225(12)
5.4.1 Introduction
225(1)
5.4.2 Confidence interval estimate of the population mean, μ (σknown)
226(2)
5.4.3 Confidence interval estimate of the population mean, μ (σunknown, n < 30)
228(4)
5.4.4 Confidence interval estimate of the population mean, μ (σtunknown, n ≥ 30)
232(3)
5.4.5 Confidence interval estimate of a population proportion
235(2)
5.5 Calculating sample size
237(6)
Techniques in practice
239(2)
Summary
241(1)
Key terms
241(1)
Further reading
242(1)
6 Introduction to parametric hypothesis testing
243(53)
Overview
243(1)
Learning objectives
243(1)
6.1 Hypothesis testing rationale
244(9)
6.1.1 Hypothesis statements H0 and H1
244(2)
6.1.2 Parametric versus non-parametric tests of difference
246(1)
6.1.3 One and two sample tests
246(1)
6.1.4 Choosing an appropriate statisitcal test
247(1)
6.1.5 Significance level
248(1)
6.1.6 Sampling distributions
248(1)
6.1.7 One and two tail tests
249(1)
6.1.8 Check t-test model assumptions
250(1)
6.1.9 Types of error
251(1)
6.1.10 P-values
251(1)
6.1.11 Critical test statistic
252(1)
6.2 One sample z-test for the population mean
253(4)
6.3 One sample t-test for the population mean
257(4)
6.4 Two sample z-test for the population mean
261(5)
6.5 Two sample z-test for the population proportion
266(3)
6.6 Two sample t-test for population mean (independent samples, equal variances)
269(5)
6.7 Two sample tests for population mean (independent samples, unequal variances)
274(5)
6.7.1 Two sample tests for independent samples (unequal variances)
274(5)
6.7.2 Equivalent non-parametric test: Mann-Whitney U test
279(1)
6.8 Two sample tests for population mean (dependent or paired samples)
279(6)
6.8.1 Two sample tests for dependent samples
279(4)
6.8.2 Equivalent non-parametric test: Wilcoxon matched pairs test
283(2)
6.9 F test for two population variances (variance ratio test)
285(5)
6.10 Calculating the size of the type II error and the statistical power
290(6)
Techniques in practice
292(2)
Summary
294(1)
Key terms
294(1)
Further reading
295(1)
7 Chi-square and non-parametric hypothesis testing
296(47)
Overview
296(1)
Learning objectives
296(1)
7.1 Chi-square tests
297(21)
7.1.1 Chi-square test of association
298(5)
7.1.2 Chi-square test for independent samples
303(4)
7.1.3 McNemar's test for matched (or dependent) pairs
307(5)
7.1.4 Chi-square goodness-of-fit test
312(6)
7.2 Non-parametric (or distribution-free) tests
318(25)
7.2.1 Sign test
318(6)
7.2.2 Wilcoxon signed rank sum test for dependent samples (or matched pairs)
324(7)
7.2.3 Mann-Whitney U test for two independent samples
331(7)
Techniques in practice
338(2)
Summary
340(1)
Key terms
341(1)
Further reading
341(2)
8 Linear correlation and regression analysis
343(63)
Overview
343(1)
Learning objectives
343(1)
8.1 Linear correlation analysis
344(18)
8.1.1 Scatter plots
344(3)
8.1.2 Covariance
347(1)
8.1.3 Pearson's correlation coefficient, r
348(5)
8.1.4 Testing the significance of linear correlation between the two variables
353(3)
8.1.5 Spearman's rank correlation coefficient
356(2)
8.1.6 Testing the significance of Spearman's rank correlation coefficient, rs
358(4)
8.2 Linear regression analysis
362(28)
8.2.1 Construct scatter plot to identify model
364(1)
8.2.2 Fit line to sample data
364(5)
8.2.3 Sum of squares defined
369(1)
8.2.4 Regression assumptions
370(2)
8.2.5 Test model reliability
372(2)
8.2.6 The use of t-test to test whether the predictor variable is a significant contributor
374(4)
8.2.7 The use of F test to test whether the predictor variable is a significant contributor
378(4)
8.2.8 Confidence interval estimate for slope β1
382(1)
8.2.9 Prediction interval for an estimate of Y
383(2)
8.2.10 Excel data analysis regression solution
385(5)
8.3 Some advanced topics in regression analysis
390(16)
8.3.1 Introduction to non-linear regression
390(7)
8.3.2 Introduction to multiple regression analysis
397(4)
Techniques in practice
401(3)
Summary
404(1)
Key terms
405(1)
Further reading
405(1)
9 Time series data and analysis
406(62)
Overview
406(1)
Learning objectives
406(1)
9.1 Introduction to time series data
407(4)
9.1.1 Stationary and non-stationary time series
407(2)
9.1.2 Seasonal time series
409(1)
9.1.3 Univariate and multivariate methods
409(1)
9.1.4 Scaling the time series
410(1)
9.2 Index numbers
411(8)
9.2.1 Simple indices
412(3)
9.2.2 Aggregate indices
415(1)
9.2.3 Deflating values
416(3)
9.3 Trend extrapolation
419(11)
9.3.1 A trend component
420(1)
9.3.2 Fitting a trend to a time series
420(3)
9.3.3 Types of trends
423(1)
9.3.4 Using a trend chart function to forecast time series
424(2)
9.3.5 Trend parameters and calculations
426(4)
9.4 Moving averages and time series smoothing
430(15)
9.4.1 Forecasting with moving averages
431(5)
9.4.2 Exponential smoothing concept
436(2)
9.4.3 Forecasting with exponential smoothing
438(7)
9.5 Forecasting seasonal series with exponential smoothing
445(5)
9.6 Forecasting errors
450(8)
9.6.1 Error measurement
450(3)
9.6.2 Types of errors
453(2)
9.6.3 Interpreting errors
455(1)
9.6.4 Error inspection
456(2)
9.7 Confidence intervals
458(10)
9.7.1 Population and sample standard errors
458(1)
9.7.2 Standard errors in time series
459(4)
Techniques in practice
463(2)
Summary
465(1)
Key terms
466(1)
Further reading
466(2)
Glossary 468(9)
Index 477