The Student Guide to MINITAB Release 14 + MINITAB Student Release 14 Statistical Software (Book + CD),9780201774696

The Student Guide to MINITAB Release 14 + MINITAB Student Release 14 Statistical Software (Book + CD)

by ; ;
Edition: 1st
ISBN13: 9780201774696
ISBN10: 0201774690
Format: Paperback
Pub. Date: 2004-07-30
Publisher(s): Pearson
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Summary

The Guide to Minitab includes both a Getting Started with Minitab section and hands-on, self-paced Tutorials designed to teach students how to use the software capabilities through a variety of approaches. the Tutorials cover all of the primary features and capabilities of MINITAB, including graphical and numerical methods for one and two or more variables, bivariate analysis, total quality management tools, time series analysis, and taking data from the web, to name a few. MINITAB is included on the CD in the back of the guide and is an easy-to-use general-purpose statistical computing package for analyzing data. It is a flexible and powerful tool that was designed from the beginning to be used by students and researchers new to statistics. It is now one of the most widely used statistics packages in the world. Minitab performs horribly tedious computations and produces accurate and professional quality graphs almost instantly. This power frees the user to focus on the exploration of the structure of the data and the interpretation of the output.

Table of Contents

Tutorial 0: Getting Started with Minitab 1(21)
0.1 Introduction to Minitab
2 (4)
What's in This Book?
3 (1)
Typographical Conventions
3 (1)
Technical Support
4(1)
Installing Minitab
4 (1)
The Minitab Menu
5 (1)
Types of Data Files
6(1)
0.2 Touring Minitab and Using Help
6 (8)
Opening Minitab
6(3)
Worksheets and the Data Window
9 (1)
Issuing Minitab Commands
10 (1)
Context-Sensitive Help
10 (1)
Using the Help Menu
11 (1)
Getting Help with Data Sets
12(2)
Exiting Minitab
14(1)
Web Site for the Book
14(1)
0.3 Sample Minitab Session
14 (8)
Getting Started
14(1)
Exploring an Existing Worksheet
15(1)
CASE STUDY: GEOLOGY-DURATION OF "OLD FAITHFUL" ERUPTIONS
15(8)
Getting Information About a Data Set
16 (3)
Creating Graphs
19 (1)
Printing a Graph
20 (1)
Exiting Minitab
21(1)
Review and Practice
21(1)
Tutorial I: Working with Data 22(37)
1.1 Opening Minitab
23(4)
CASE STUDY: HEALTH MANAGEMENT-NUTRITIONAL ANALYSIS
23(4)
1.2 Entering Data
27(1)
1.3 Correcting Mistakes
28 (1)
1.4 Text and Numeric Data
28 (1)
1.5 Saving Data
29(1)
1.6 Naming Columns
30(1)
1.7 Printing from the Data Window
31 (1)
1.8 Moving in the Data Window
32 (1)
1.9 Leaving Minitab
33(1)
1.10 Retrieving Data
33(1)
1.11 Manipulating Data Using the Calculator Command
34(2)
1.12 Copying Columns
36(4)
1.13 Opening a Minitab Stored Data File
40(2)
CASE STUDY: MANAGEMENT-SALARY STRUCTURE
40(20)
Getting Information About a Data Set
41(1)
1.14 Deleting and Inserting Rows
42(3)
1.15 Deleting Columns
45(1)
1.16 Viewing Information About the Data Set
45 (1)
1.17 Exporting Data to Excel
46 (2)
1.18 Importing Data from Excel
48(2)
Minitab Command Summary
50 (2)
Review and Practice
52(7)
Tutorial 2: Summarizing, Transforming, and Manipulating Data 59(33)
2.1 Summarizing Cases and Rounding
60(5)
CASE STUDY: EDUCATION-CLASS EVALUATION
60 (5)
2.2 Summarizing Columns
65(1)
2.3 Using Session Commands
66(3)
2.4 Coding Data
69 (2)
2.5 Ranking Data
71 (1)
2.6 Sorting Data
72(2)
2.7 Standardizing Data
74(1)
2.8 Creating Subsets
75(1)
2.9 Combining Data Using the Stack Option
76 (2)
2.10 Separating Data Using the Unstack Option
78 (2)
2.11 Printing the Results of Your Analysis
80(3)
2.12 Creating a Text File
83(2)
Minitab Command Summary
85(1)
Review and Practice
86(6)
Tutorial 3: Data Analysis for One Variable 92(40)
3.1 Creating a Project
93(2)
CASE STUDY: PUBLIC HEALTH-INFANT NUTRITION
93(2)
3.2 Summarizing Qualitative Variables
95(2)
3.3 Creating Bar Charts
97(6)
Naming Graphs
98(1)
The Project Manager
99(1)
Bar Graphs Using Summarized Data
100 (1)
Saving Graphs
101(1)
Percentages Using Summarized Data
102(1)
3.4 Creating Pie Charts
103(2)
3.5 Quantitative Variables: Creating Histograms
105(2)
3.6 Creating Stem-and-Leaf Displays
107(4)
3.7 Creating Dotplots
111(1)
3.8 Creating Individual Value Plots
112(1)
3.9 Creating Boxplots
113(2)
3.10 Quantitative Variables: Summarizing Data Numerically
115(4)
3.11 Using StatGuide and the Glossary
119(1)
3.12 Constructing Other Descriptive Statistics
120 (1)
3.13 Copying Text Output into ReportPad and Microsoft Word
121(2)
3.14 Saving and Reopening a Project
123(2)
MINITAB AT WORK: EDUCATION
124(1)
Minitab Command Summary
125 (1)
Review and Practice
126(6)
Tutorial 4: Data Analysis: Comparing Groups 132(26)
4.1 Contingency Tables
133(3)
CASE STUDY: PUBLIC HEALTH-INFANT NUTRITION (CONTINUED)
133(3)
4.2 Cluster and Stack Bar Charts
136 (4)
4.3 Comparing Dotplots
140(1)
CASE STUDY: SPORTS-BASEBALL STADIUMS
140(1)
4.4 Comparing Individual Value Plots
141 (1)
4.5 Comparing Boxplots
142(1)
4.6 Describing Subgroups
143(3)
4.7 Using Charts to Display Descriptive Statistics
146(3)
4.8 Exporting Graphs
149(2)
Minitab Command Summary
151(1)
Review and Practice
152(6)
Tutorial 5: Examining Relationships Between Two Quantitative Variables 158(41)
5.1 Creating Scatterplots
158(7)
CASE STUDY: SPORTS-BASEBALL STADIUMS (CONTINUED)
159(19)
Using Crosshairs
164(1)
5.2 Adding a Grouping Variable to a Scatterplot
165(3)
Paneling a Scatterplot
167(1)
5.3 Viewing the History Folder
168(2)
5.4 Creating Marginal Plots
170(1)
5.5 Computing Covariance
171(1)
5.6 Computing Correlation
172(2)
5.7 Computing the Least Squares/Regression Line
174(1)
5.8 Displaying the Least Squares/Regression Line
175(3)
5.9 Creating Plots on Which X Represents Time
178(2)
CASE STUDY: BUSINESS-COMPETITION
178(2)
5.10 Overlaying Plots
180 (2)
5.11 Exporting Data
182(5)
CASE STUDY: SPORTS-BASEBALL STADIUMS (CONTINUED)
182(18)
Exporting Formatted Data
184(2)
Exporting Data to an Excel Spreadsheet
186 (1)
5.12 Importing Data
187(4)
Renaming a Worksheet in Minitab
188(1)
Importing Formatted Text Data Files
188(2)
Importing an Excel File
190 (1)
Minitab Command Summary
191 (2)
Review and Practice
193(6)
Tutorial 6: Distributions and Random Data 199(29)
6.1 Calculating Binomial Probabilities
200(7)
CASE STUDY: BIOLOGY-BLOOD TYPES
200 (20)
Individual Binomial Probabilities
200 (4)
Cumulative Binomial Probabilities
204(3)
6.2 Generating Random Data from a Discrete Distribution
207(3)
CASE STUDY: MANAGEMENT-ENTREPRENEURIAL STUDIES
207(3)
6.3 Generating Random Data from a Normal Distribution
210(2)
CASE STUDY: PHYSIOLOGY-HEIGHTS
211(1)
6.4 Checking Data for Normality
212 (3)
The Normal Probability Plot
213(2)
6.5 Determining Cumulative Probabilities and Inverse Cumulative Probabilities for the Normal Distribution
215(3)
6.6 Sampling from a Column
218(2)
MINITAB AT WORK: PUBLIC SAFETY
220(1)
Minitab Command Summary
220 (3)
Review and Practice
223(5)
Tutorial 7: Inferences from One Sample 228(27)
7.1 Testing a Hypothesis About μ When σ is Known
229(5)
CASE STUDY: SOCIOLOGY-AGE AT DEATH
229(5)
7.2 Computing a Confidence Interval for μ When σ Is Known
234(1)
7.3 Sample Size for Estimating μ When σ is Known
235(2)
7.4 Inferences about μ When σ Is Unknown
237 (4)
The t-Test and Confidence Interval with Summarized Data
239(2)
7.5 Inferences About a Population Proportion
241(4)
CASE STUDY: HEALTH CARE-WORK DAYS LOST TO PAIN
241(4)
7.6 Computing the Power of a Test
245(4)
MINITAB AT WORK: RETAILING
249(1)
Minitab Command Summary
249 (1)
Review and Practice
250(5)
Tutorial 8: Inferences from Two Samples 255(28)
8.1 Comparing Population Means from Two Independent Samples
256(9)
CASE STUDY: SOCIOLOGY-AGE AT DEATH (CONTINUED)
256(9)
Two-Sample t-tests Using Stacked Data
256 (4)
Using Help to Find a Formula
260(2)
Two-Sample t-Tests Using Unstacked Data
262(2)
Two-Sample t-Tests Using Summarized Data
264(1)
Obtaining a 95% Two-Sided Confidence Interval for μF - μM
264(1)
8.2 Inference on the Mean of Paired Data
265(4)
CASE STUDY: HEALTH CARE-CEREAL AND CHOLESTEROL
265(4)
8.3 Sample Size and Power for Comparing the Means of Two Independent Samples
269(3)
CASE STUDY: WELFARE REFORM-ERRORS IN GRANT DETERMINATION
269(3)
8.4 Comparing Population Proportions from Two Independent Samples
272(3)
CASE STUDY: HEALTH CARE-WORK DAYS LOST TO PAIN (CONTINUED)
272 (5)
Comparing Two Proportions Using Summarized Data
274(1)
8.5 Sample Size and Power for Comparing Two Independent Proportions
275(2)
MINITAB AT WORK: SCIENTIFIC RESEARCH
277(1)
Minitab Command Summary
277 (1)
Review and Practice
278(5)
Tutorial 9: Comparing Population Means: Analysis of Variance 283(29)
9.1 Comparing the Means of Several Populations
284(5)
CASE STUDY: CHILD DEVELOPMENT-INFANT ATTENTION SPANS
284(5)
9.2 Checking the Assumptions for a One-Way ANOVA
289(2)
9.3 Performing Tukey's Multiple Comparisons Test
291(3)
9.4 Comparing the Means of Several Populations with Responses in Separate Columns
294 (2)
9.5 Performing a Two-Factor Analysis of Variance
296(10)
CASE STUDY: PSYCHOLOGY-MEASURING DEPTH PERCEPTION
296(17)
The Two-Way ANOVA
297(4)
Checking the Assumptions for the F-tests in a Two-Way ANOVA
301(2)
The Interactions Plot
303(1)
Creating Factor Levels
304 (2)
Minitab Command Summary
306
Review and Practice
107(205)
Tutorial 10: Fundamentals of Linear Regression 312(25)
10.1 Fitting a Straight Line to Data: Simple Linear Regression
313(8)
CASE STUDY: INSTITUTIONAL RESEARCH-TUITION MODELING
313(18)
A Confidence Interval for the Population Slope
317(1)
Obtaining Residuals
318 (2)
The Fitted Line Plot
320(1)
10.2 Computing Response Variable Estimates
321 (3)
10.3 Performing a Quadratic Regression
324(2)
Using Transformations
326(1)
10.4 Performing Multiple Linear Regression
326 (2)
10.5 Obtaining Multiple Linear Regression Response Variable Estimates
328(3)
MINITAB AT WORK: HUMAN RESOURCES
331(1)
Minitab Command Summary
331 (1)
Review and Practice
332(5)
Tutorial 11: Building Regression Models 337(41)
11.1 The Importance of Graphs in Regression
338(7)
CASE STUDY: DATA ANALYSIS-IMPORTANCE OF GRAPHS
338(7)
11.2 Identifying Collinearity
345(4)
CASE STUDY: INSTITUTIONAL RESEARCH-TUITION MODELING (CONTINUED)
345(4)
11.3 Verifying Linear Regression Assumptions
349(6)
Storing the Residuals
349(2)
Checking the Normality Assumption
351 (1)
Using Scatterplots to Verify the Homoscedasity Assumption
351(2)
Checking the Independence Assumption with a Time Series Plot
353(2)
11.4 Examining Unusual Observations
355(2)
Cook's Distance
357(1)
11.5 Incorporating an Indicator (Dummy) Variable into a Model
357(5)
Interpreting the Regression Coefficient for an Indicator Variable
361(1)
11.6 Performing Best Subsets Regression
362 (6)
11.7 Performing a Binary Logistic Regression
368 (4)
Minitab Command Summary
372(1)
Review and Practice
373(5)
Tutorial 12: Analyzing Qualitative Data 378(25)
12.1 Comparing an Observed Distribution of Counts to a Hypothesized Distribution
379(5)
CASE STUDY: MANAGEMENT-ENTREPRENEURIAL STUDIES (CONTINUED)
379(5)
12.2 A Minitab Exec Macro for a Chi-Square Goodness-of-Fit Test
384(4)
12.3 The Chi-Square Test for Independence for Two Qualitative Variables in a Contingency Table
388(6)
CASE STUDY: HUMAN RESOURCES-EMPLOYMENT STATISTICS
388(6)
12.4 The Chi-Square Test for Independence for Two Qualitative Variables Using Raw Data
394 (4)
Minitab Command Summary
398(1)
Review and Practice
399(4)
Tutorial 13: Analyzing Data with Nonparametric Methods 403(23)
13.1 The Runs Test for Randomness
404(4)
CASE STUDY: METEOROLOGY-SNOWFALL
404(4)
13.2 Testing a Hypothesis About the Population Median Using the Sign Test
408(2)
CASE STUDY: HEALTH CARE-CEREAL AND CHOLESTEROL (CONTINUED)
408(2)
13.3 Estimating the Population Median with the 1-Sample Sign Confidence Interval Estimate
410(1)
13.4 Testing Hypotheses About the Population Median Using the Wilcoxon Test
411(1)
13.5 Estimating the Population Median with the Wilcoxon Confidence Interval Estimate
412 (1)
13.6 Comparing the Medians of Two Independent Populations
413(4)
CASE STUDY: SOCIOLOGY-AGE AT DEATH (CONTINUED)
413(4)
13.7 Computing the Medians of K Independent Populations Using the Kruskal-Wallis Test
417(4)
CASE STUDY: CHILD DEVELOPMENT-INFANT ATTENTION SPANS (CONTINUED)
417(3)
MINITAB AT WORK: MEDICAL DIAGNOSTICS
420(1)
Minitab Command Summary
421 (1)
Review and Practice
422(4)
Tutorial 14: Time Series Analysis 426(30)
14.1 Performing a Trend Analysis of a Time Series
427(3)
CASE STUDY: ENVIRONMENT-TEMPERATURE VARIATIONS
427(3)
14.2 Performing a Classical Decomposition of a Time Series
430(5)
14.3 Autocorrelation and Partial Autocorrelation Plots
435(4)
Autocorrelation
435(2)
Partial Autocorrelations
437(2)
14.4 Transforming a Time Series
439 (2)
Lagging Data
439(1)
Computing Differences
440(1)
14.5 Performing a Box-Jenkins ARIMA Analysis of a Time Series
441(6)
Constructing a Seasonal Model
444 (3)
14.6 Forecasting with ARIMA
447(2)
Plotting the ARIMA Forecasts
448(1)
14.7 Comparing the Two Forecasting Models
449(2)
MINITAB AT WORK: STOCK MARKET
451(1)
Minitab Command Summary
451 (1)
Review and Practice
452(4)
Tutorial 15: Total Quality Management Tools 456(27)
15.1 Creating a Cause-and-Effect Diagram
457(2)
CASE STUDY: EDUCATION-FACULTY SURVEY
457(2)
15.2 Creating a Pareto Chart
459 (3)
15.3 Constructing an Xbar Chart
462(4)
CASE STUDY: PRODUCTION-QUALITY CONTROL CHARTS
462(4)
15.4 Constructing a Range Chart
466(3)
15.5 Constructing an Individuals Chart
469 (1)
15.6 Constructing a Moving Range Chart
470 (3)
15.7 Constructing a Proportion Chart
473(4)
MINITAB AT WORK: QUALITY MANAGEMENT
476(1)
Minitab Command Summary
477 (1)
Review and Practice
478(5)
Appendix A: Data Sets 483(38)
Academe.mtw
484 (1)
AgeDeath.mtw
484(1)
Asses.mtw
485 (1)
Baby.mtw
485 (1)
Backpain.mtw
486(1)
BallparkData.mtw
486(1)
BodyTemp.mtw
486(1)
Candya.mtw-Candyc.mtw
487 (1)
Candya.mtw
487(1)
Candyb.mtw
487(1)
Candyc.mtw
487(1)
Carphone.mtw
488(1)
Chol.mtw
488(1)
CollMass.mtw and CollMass2.mtw
488 (1)
Compliance.mtw
489 (1)
CongressSalary.mtw
490 (1)
Cotinine.mtw
490(1)
CP12.mtw
490 (1)
Depth.mtw
490(1)
DJC20012002.mtw,DJC20012002a.mtw and DJC20012002b.mtw
491 (1)
Donner.mtw
492(1)
Drive.mtw
492 (1)
DrivingCosts.mtw
492 (1)
DrugMarkup.mtw
493(1)
Election2.mtw
493 (1)
EMail.mtw
493 (1)
Employeelnfo.mtw
493 (1)
Endowment.mtw
494 (1)
ExamScores.mtw
494(1)
Fja.mtw
494 (1)
Force.mtw
495 (1)
GasData.mtw
495 (1)
Height.mtw
495 (1)
Homes.mtw
496 (1)
Infants.mtw
496 (1)
Jeans.mtw
497 (1)
Lakes.mtw
498 (1)
Lotto.mtw
499 (1)
Marathon2.mtw
499(1)
Marks.mtw
499 (1)
MBASurvey.mtw
500(1)
Mercedes.mtw
500 (1)
MLBGameCost.mtw
500 (1)
MnWage2.mtw
501 (1)
MonthlySnow
501 (1)
Movies.mtw
501(1)
Murders.mtw and Murderu.mtw
502(1)
Murders.mtw
502(1)
Murderu.mtw
502 (1)
MusicData.mtw
503 (1)
NHL2003.mtw
503 (1)
Note02.mtw
504(1)
OldFaithful.mtw
504 (1)
OpenHouse.mtw
504 (1)
PayData.mtw
505 (1)
PhoneRates.mtw
505 (1)
Pizza2.mtw
505(1)
Process.mtw
506(1)
Prof.mtw
506(1)
Pubs.mtw
507(1)
PulseA.mtw
507(1)
Radlev.mtw
508(1)
Randomlntegers.mtw
508(1)
Rivera.mtw - Rivere.mtw and Rivers.mtw
509 (1)
Riverc2.mtw
510(1)
Salary02.mtw
510 (1)
SBP.mtw
511(1)
SchoolsData.mtw
511 (1)
Sleep.mtw
512(1)
SP5002.mtw
512(1)
SPCarData.mtw
512 (1)
SpeedCom.mtw
513 (1)
Stores2.mtw
513(1)
Survey.mtw
514(1)
TBi112.mtw
514(1)
Temco.mtw
514(1)
Textbooks.mtw
515 (1)
Top25Stars.mtw
516 (1)
Tvhrs.mtw
516(1)
TwinsYankees.mtw
517 (1)
TwoTowns.mtw
518 (1)
UGradSurvey.mtw
518 (1)
USAArrivals.mtw
519 (1)
USDemData.mtw
519 (1)
WastesData.mtw
519 (1)
YearlySnow.mtw
520 (1)
YogurtData.mtw
520(1)
Appendix B: Minitab Menus and Toolbars 521(6)
Menus
522 (3)
Toolbars
525(2)
Index 527 (14)
Credits 541

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