Business statistics in practice / Bruce L. Bowerman, Richard T. O'Connell ; with MegaStat software and other contributions by J. Burdene Orris.
Series: The McGraw-Hill/Irwin series operations and decision sciencesPublication details: Boston ; New York : McGraw-Hill/Irwin, c2007.Edition: 4th editionDescription: xxi, 883 p. : col. ill. ; 29 cmISBN:- 9780072977479
- 0072977477 (alk. paper)
- 9780073252919
- 0073252913
- 9780073191867 (CDROM)
- 0073191868 (CDROM)
- 519.502 22 BOW
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Contents;
1. An Introduction to Business Statistics
populations and samples
sampling a population of existing units
sampling a process
e.tc
2. Descriptive Statistics
Describing the shape of a distribution
Describing a central tendency
Measures of variation
e.tc
3. Probability
The concept of probability
Sample spaces and events
Some elementary probability rules
e.tc
4. Discrete Random Variables
Two types of random variables
Discrete probability distributions
The binomial distribution
e.tc
5. Continuous Random Variables
Continuous probability distributions
The uniform distribution
The normal probability distribution
e.tc
6. Sampling Distributions
the sampling distribution of the sample mean
the sampling distribution of the sample proportion
simulating sampling distributions using MINITAB
7. Confidence Intervals
Based confidence intervals for a population mean: known
Based confidence intervals for a population mean: Unknown
sample size determination
e.tc
8. Hypothesis Testing
The null and alternative hypothesis and errors in hypothesis testing
tests about a population mean
tests about a population mean
e.tc
9. Statistical Inferences Based on Two Samples
comparing concepts of experimental design
one-way analysis of variance
the randomized block design
e.tc
10. Experimental Design and Analysis of Variance
basic concepts of experimental design
one way analysis of variance
the randomized block design
e.tc
11. Simple Linear Regression Analysis
the simple linear regression model
the least squares estimates, and point estimation and prediction
e.tc
12. Multiple Regression and Model Building
basic multiple regression
the multiple regression model
the least squares estimates and point estimation and prediction
e.tc
13. Time Series Forecasting
time series components and models
time series regression : basic models
e.tc
14. Process Improvement Using Control Charts
quality: its meaning and a historical perspective
statistical process control and causes of process variation
e.tc
15. Nonparametric Methods
the sign test: a hypothesis test about the median
the Wilcoxon rank sum test
e.tc
16. Chi-Square Tests
chi-square goodness of fit tests
a chi square test for independence
e.tc
17. Decision Theory
Bayes' theorem
introduction to decision theory
decision making using posterior probabilities
e.tc
Includes bibliographical references and indexes.
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