Schaum's outline of theory and problems of business statistics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
McGraw-Hill Publishing Co.
1996
|
| Ausgabe: | 3. ed. |
| Schriftenreihe: | Schaum's outline series
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIII, 410 S. graph. Darst. |
| ISBN: | 0070340269 |
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Datensatz im Suchindex
| _version_ | 1804138789795266560 |
|---|---|
| adam_text | Contents
Chapter 1 ANALYZING BUSINESS DATA 1
1.1 Definition of Business Statistics 1
1.2 Descriptive and Inferential Statistics 1
1.3 Types of Applications in Business 1
1.4 Discrete and Continuous Variables 2
1.5 Obtaining Data Through Direct Observation vs. Surveys 2
1.6 Methods of Random Sampling 2
1.7 Other Sampling Methods 3
1.8 Using Computer Software to Generate Random Numbers 4
Chapter 2 STATISTICAL PRESENTATIONS AND GRAPHICAL
ANALYSIS 9
2.1 Frequency Distributions 9
2.2 Class Intervals 9
2.3 Histograms and Frequency Polygons 10
2.4 Frequency Curves 11
2.5 Cumulative Frequency Distributions 12
2.6 Relative Frequency Distributions 13
2.7 The And-Under Type of Frequency Distribution 14
2.8 Stem-and-Leaf Diagrams 14
2.9 Dotplots 15
2.10 Pareto Charts 15
2.11 Bar Charts and Line Graphs 16
2.12 Run Charts 17
2.13 Pie Charts 18
Chapter 3 DESCRIBING BUSINESS DATA: MEASURES OF LOCATION . . 39
3.1 Measures of Location in Data Sets 39
3.2 The Arithmetic Mean 39
3.3 The Weighted Mean 39
3.4 The Median 40
3.5 The Mode 40
3.6 Relationship Between the Mean and the Median 41
3.7 Mathematical Criteria Satisfied by the Median and the Mean 41
3.8 Use of the Mean, Median, and Mode 42
3.9 Use of the Mean in Statistical Process Control 42
3.10 Quartiles, Deciles, and Percentiles 43
3.11 Computer Output 43
vii
viii CONTENTS
Chapter 4 DESCRIBING BUSINESS DATA: MEASURES OF
VARIABILITY 51
4.1 Measures of Variability in Data Sets 51
4.2 The Range 51
4.3 Modified Ranges 51
4.4 Box Plots 52
4.5 The Mean Absolute Deviation (MAD) 52
4.6 The Variance and Standard Deviation 53
4.7 Simplified Calculations for the Variance and Standard Deviation 54
4.8 The Mathematical Criterion Associated with the Variance and Standard
Deviation 55
4.9 Use of the Standard Deviation in Data Description 55
4.10 Use of the Range and Standard Deviation in Statistical Process Control 56
4.11 The Coefficient of Variation 57
4.12 Pearson s Coefficient of Skewness 57
4.13 Computer Output 58
Chapter 5 PROBABILITY 68
5.1 Basic Definitions of Probability 68
5.2 Expressing Probability 69
5.3 Mutually Exclusive and Nonexclusive Events 70
5.4 The Rules of Addition 70
5.5 Independent Events, Dependent Events, and Conditional Probability 71
5.6 The Rules of Multiplication 72
5.7 Bayes Theorem 74
5.8 Joint Probability Tables 75
5.9 Permutations 76
5.10 Combinations 77
Chapter 6 PROBABILITY DISTRIBUTIONS FOR DISCRETE RANDOM
VARIABLES: BINOMIAL HYPERGEOMETRIC, AND POISSON . . 94
6.1 What Is a Random Variable? 94
6.2 Describing a Discrete Random Variable 94
6.3 The Binomial Distribution 96
6.4 The Binomial Variable Expressed by Proportions 97
6.5 The Hypergeometric Distribution 98
6.6 The Poisson Distribution 99
6.7 Poisson Approximation of Binomial Probabilities 100
6.8 Computer Applications 101
CONTENTS ix
Chapter 7 PROBABILITY DISTRIBUTIONS FOR CONTINUOUS RANDOM
VARIABLES: NORMAL AND EXPONENTIAL 114
7.1 Continuous Random Variables 114
7.2 The Normal Probability Distribution 114
7.3 Percentile Points for Normally Distributed Variables 117
7.4 Normal Approximation of Binomial Probabilities 118
7.5 Normal Approximation of Poisson Probabilities 119
7.6 The Exponential Probability Distribution 120
7.7 Computer Applications 121
Chapter * SAMPLING DISTRIBUTIONS AND CONFIDENCE INTERVALS
FOR THE MEAN 133
8.1 Point Estimation of a Population or Process Parameter 133
8.2 The Concept of a Sampling Distribution 133
8.3 Sampling Distribution of the Mean 134
8.4 The Central Limit Theorem 135
8.5 Determining Probability Values for the Sample Mean 136
8.6 Confidence Intervals for the Mean Using the Normal Distribution 137
8.7 Determining the Required Sample Size for Estimating the Mean 138
8.8 The t Distribution and Confidence Intervals for the Mean 139
8.9 Summary Table for Interval Estimation of the Population Mean 140
8.10 Computer Output 140
Chapter 9 OTHER CONFIDENCE INTERVALS 150
9.1 Confidence Intervals for the Difference Between Two Means Using the
Normal Distribution 150
9.2 The t Distribution and Confidence Intervals for the Difference Between Two
Means 151
9.3 Confidence Intervals for the Population Proportion 152
9.4 Determining the Required Sample Size for Estimating the Proportion 152
9.5 Confidence Intervals for the Difference Between Two Proportions 153
9.6 The Chi-Square Distribution and Confidence Intervals for the Variance and
Standard Deviation 154
9.7 Computer Output 155
Chapter 10 TESTING HYPOTHESES CONCERNING THE VALUE OF THE
POPULATION MEAN 163
10.1 Introduction 163
10.2 Basic Steps in Hypothesis Testing by the Critical Value Approach 163
10.3 Testing a Hypothesis Concerning the Mean by Use of the Normal
Distribution 164
10.4 Type I and Type II Errors in Hypothesis Testing 167
10.5 Determining the Required Sample Size for Testing the Mean 169
10.6 Testing a Hypothesis Concerning the Mean by Use of the t Distribution .... 170
x CONTENTS
10.7 The P-Value Approach to Testing Hypotheses Concerning the Population
Mean 171
10.8 The Confidence Interval Approach to Testing Hypotheses Concerning the
Mean 172
10.9 Testing with Respect to the Process Mean in Statistical Process Control .... 172
10.10 Summary Table for Testing a Hypothesized Value of the Mean 173
Chapter 11 TESTING OTHER HYPOTHESES 186
11.1 Testing the Difference Between Two Means Using the Normal
Distribution 186
11.2 Testing the Difference Between Means Using the t Distribution 188
11.3 Testing the Difference Between Means Based on Paired Observations 188
11.4 Testing a Hypothesis Concerning the Value of the Population Proportion ... 190
11.5 Determining the Required Sample Size for Testing the Proportion 191
11.6 Testing with Respect to the Process Proportion in Statistical Process
Control 191
11.7 Testing the Difference Between Two Population Proportions 192
11.8 Testing a Hypothesized Value of the Variance Using the Chi-Square
Distribution 193
11.9 Testing with Respect to Process Variability in Statistical Process Control ... 193
11.10 The F Distribution and Testing the Equality of Two Population Variances . . 194
11.11 Alternative Approaches to Testing Null Hypotheses 195
11.12 Computer Output 195
Chapter 12 THE CHI-SQUARE TEST 206
12.1 General Purpose of the Chi-Square Test 206
12.2 Goodness of Fit Tests 206
12.3 Tests for the Independence of Two Categorical Variables (Contingency
Table Tests) 208
12.4 Testing Hypotheses Concerning Proportions 210
12.5 Computer Output 213
Chapter 13 ANALYSIS OF VARIANCE 228
13.1 Basic Rationale Associated with Testing the Differences Among
Several Population Means 228
13.2 One-Factor Completely Randomized Design (One-Way ANOVA) 229
13.3 Two-Way Analysis of Variance (Two-Way ANOVA) 230
13.4 The Randomized Block Design (Two-Way ANOVA, One
Observation per Cell) 230
13.5 Two-Factor Completely Randomized Design (Two-Way
ANOVA, n Observations per Cell) 231
13.6 Additional Considerations 232
13.7 Computer Applications 233
CONTENTS xi
Chapter 14 LINEAR REGRESSION AND CORRELATION ANALYSIS 248
14.1 Objectives and Assumptions of Regression Analysis 248
14.2 The Scatter Plot 248
14.3 The Method of Least Squares for Fitting a Regression Line 249
14.4 Residuals and Residual Plots 250
14.5 The Standard Error of Estimate 250
14.6 Inferences Concerning the Slope 251
14.7 Confidence Intervals for the Conditional Mean 251
14.8 Prediction Intervals for Individual Values of the Dependent Variable 252
14.9 Objectives and Assumptions of Correlation Analysis 252
14.10 The Coefficient of Determination 253
14.11 The Coefficient of Correlation 254
14.12 The Covariance Approach to Understanding the Correlation Coefficient .... 255
14.13 Significance Testing with Respect to the Correlation Coefficient 255
14.14 Pitfalls and Limitations Associated with Regression and Correlation
Analysis 256
14.15 Computer Output 256
Chapter 15 MULTIPLE REGRESSION AND CORRELATION 268
15.1 Objectives and Assumptions of Multiple Linear Regression Analysis 268
15.2 Additional Concepts in Multiple Regression Analysis 268
15.3 The Use of Indicator (Dummy) Variables 269
15.4 Residuals and Residual Plots 270
15.5 Analysis of Variance in Linear Regression Analysis 270
15.6 Objectives and Assumptions of Multiple Correlation Analysis 272
15.7 Additional Concepts in Multiple Correlation Analysis 272
15.8 Pitfalls and Limitations Associated with Multiple Regression and
Multiple Correlation Analysis 273
15.9 Computer Output 273
Chapter 16 TIME SERIES ANALYSIS AND BUSINESS FORECASTING 282
16.1 The Classical Time Series Model 282
16.2 Trend Analysis 283
16.3 Analysis of Cyclical Variations 284
16.4 Measurement of Seasonal Variations 284
16.5 Applying Seasonal Adjustments 285
16.6 Forecasting Based on Trend and Seasonal Factors 285
16.7 Cyclical Forecasting and Business Indicators 286
16.8 Forecasting Based on Moving Averages 287
16.9 Exponential Smoothing as a Forecasting Method 287
16.10 Other Forecasting Methods That Incorporate Smoothing 288
16.11 Computer Output 289
xii CONTENTS
Chapter 17 INDEX NUMBERS FOR BUSINESS AND ECONOMIC DATA ... 304
17.1 Introduction 304
17.2 Construction of Simple Indexes 304
17.3 Construction of Aggregate Price Indexes 304
17.4 Link Relatives 305
17.5 Shifting the Base Period 305
17.6 Splicing Two Series of Index Numbers 305
17.7 The Consumer Price Index (CPI) 306
17.8 Purchasing Power and the Deflation of Time Series Values 306
17.9 The Producer Price Index (PPI) 306
17.10 The Dow Jones Stock Price Averages 306
17.11 The Index of Industrial Production 307
Chapter 18 DECISION ANALYSIS: PAYOFF TABLES AND DECISION
TREES 315
18.1 The Structure of Payoff Tables 315
18.2 Decision Making Based upon Probabilities Alone 316
18.3 Decision Making Based upon Economic Consequences Alone 317
18.4 Decision Making Based upon Both Probabilities and Economic
Consequences: The Expected Payoff Criterion 319
18.5 Decision Tree Analysis 320
18.6 Expected Utility as the Decision Criterion 321
Chapter 19 DECISION ANALYSIS: THE USE OF SAMPLE
INFORMATION 335
19.1 The Expected Value of Perfect Information (EVPI) 335
19.2 Prior and Posterior Probability Distributions 336
19.3 The Value of Sample Information That Has Already Been Obtained 337
19.4 The Expected Value of Sample Information (EVSI) Prior to Sampling 339
19.5 Expected Net Gain from Sampling (ENGS) and Optimum Sample Size 342
19.6 Decision Analysis vs. Classical Decision Procedures 344
Chapter 20 STATISTICAL PROCESS CONTROL 352
20.1 Total Quality Management 352
20.2 Statistical Quality Control 352
20.3 Types of Variation in Processes 353
20.4 Control Charts 354
20.5 Control Charts for the Process Mean: X Charts 355
20.6 Standard Tests Used for Interpreting X Charts 356
CONTENTS xiii
20.7 Control Charts for the Process Standard Deviation: s Charts 357
20.8 Control Charts for the Process Range: R Charts 358
20.9 Control Charts for the Process Proportion: p Charts 359
Chapter 21 NONPARAMETRIC STATISTICS 372
21.1 Scales of Measurement 372
21.2 Parametric vs. Nonparametric Statistical Methods 372
21.3 The Runs Test for Randomness 373
21.4 One Sample: The Sign Test 373
21.5 One Sample: The Wilcoxon Test 374
21.6 Two Independent Samples: The Mann-Whitney Test 374
21.7 Paired Observations: The Sign Test 375
21.8 Paired Observations: The Wilcoxon Test 376
21.9 Several Independent Samples: The Kruskal-Wallis Test 376
Appendix 1 TABLE OF RANDOM NUMBERS 387
Appendix 2 BINOMIAL PROBABILITIES 388
Appendix 3 VALUES OF e~x 391
Appendix 4 POISSON PROBABILITIES 392
Appendix 5 PROPORTIONS OF AREA FOR THE STANDARD NORMAL
DISTRIBUTION 396
Appendix 6 PROPORTIONS OF AREA FOR THE t DISTRIBUTION 397
Appendix 7 PROPORTIONS OF AREA FOR THE Z2 DISTRIBUTION 398
Appendix 8 VALUES OF F EXCEEDED WITH PROBABILITIES OF
5 AND 1% 399
Appendix 9 FACTORS FOR CONTROL CHARTS 402
Appendix 10 CRITICAL VALUES OF T IN THE WILCOXON TEST 403
INDEX 405
|
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| title | Schaum's outline of theory and problems of business statistics |
| title_auth | Schaum's outline of theory and problems of business statistics |
| title_exact_search | Schaum's outline of theory and problems of business statistics |
| title_full | Schaum's outline of theory and problems of business statistics Leonard J. Kazmier |
| title_fullStr | Schaum's outline of theory and problems of business statistics Leonard J. Kazmier |
| title_full_unstemmed | Schaum's outline of theory and problems of business statistics Leonard J. Kazmier |
| title_short | Schaum's outline of theory and problems of business statistics |
| title_sort | schaum s outline of theory and problems of business statistics |
| topic | Wirtschaftsstatistik (DE-588)4066517-3 gnd Statistik (DE-588)4056995-0 gnd Wirtschaftswissenschaften (DE-588)4066528-8 gnd Methode (DE-588)4038971-6 gnd |
| topic_facet | Wirtschaftsstatistik Statistik Wirtschaftswissenschaften Methode Aufgabensammlung Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017289066&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT kazmierleonardj schaumsoutlineoftheoryandproblemsofbusinessstatistics |