Statistics for business and financial economics:
Gespeichert in:
| Hauptverfasser: | , , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
2013
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| Ausgabe: | 3. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XLVIII, 1206 S. graph. Darst. |
| ISBN: | 9781461458968 |
Internformat
MARC
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| 100 | 1 | |a Lee, Cheng F. |e Verfasser |0 (DE-588)129807907 |4 aut | |
| 245 | 1 | 0 | |a Statistics for business and financial economics |c Cheng-Few Lee ; John C. Lee ; Alice C. Lee |
| 250 | |a 3. ed. | ||
| 264 | 1 | |a New York [u.a.] |b Springer |c 2013 | |
| 300 | |a XLVIII, 1206 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Commercial statistics | |
| 650 | 4 | |a Finance / Statistical methods | |
| 650 | 0 | 7 | |a Wirtschaftsstatistik |0 (DE-588)4066517-3 |2 gnd |9 rswk-swf |
| 655 | 7 | |0 (DE-588)4123623-3 |a Lehrbuch |2 gnd-content | |
| 689 | 0 | 0 | |a Wirtschaftsstatistik |0 (DE-588)4066517-3 |D s |
| 689 | 0 | |C b |5 DE-604 | |
| 700 | 1 | |a Lee, John C. |e Verfasser |4 aut | |
| 700 | 1 | |a Lee, Alice C. |e Verfasser |0 (DE-588)132014335 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-4614-5897-5 |
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| 856 | 4 | 2 | |m Digitalisierung UB Augsburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188509&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-026188509 | |
Datensatz im Suchindex
| _version_ | 1808587940355375104 |
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Part I Introduction and Descriptive Statistics
1 Introduction. 3
1.1 The Role of Statistics in Business and Economics. 3
1.2 Descriptive Versus Inferential Statistics. 5
1.3 Deductive Versus Inductive Analysis in Statistics. 10
1.4 Summary. 10
Questions and Problems. 11
2 Data Collection and Presentation. 15
2.1 Introduction. 16
2.2 Data Collection. 16
2.3 Data Presentation: Tables. 19
2.4 Data Presentation: Charts and Graphs. 19
2.5 Applications. 24
2.6 Summary. 30
Questions and Problems. 30
Appendix 1: Using Microsoft Excel to Draw Graphs. 45
Appendix 2: Stock Rates of Return and Market Rates of Return. 47
Appendix 3: Financial Statements and Financial Ratio Analysis. 51
3 Frequency Distributions and Data Analyses. 65
3.1 Introduction. 65
3.2 Tally Table for Constructing a Frequency Table. 66
3.3 Three Other Frequency Tables. 70
3.4 Graphical Presentation of Frequency Distribution. 72
3.4.1 Histograms. 72
3.4.2 Stem-and-Leaf Display. 76
3.4.3 Frequency Polygon. 80
3.4.4 Pie Chart. 81
3.5 Further Economic and Business Applications. 82
3.5.1 Lorenz Curve. 82
3.5.2 Stock and Market Rate of Return. 84
3.5.3 Interest Rates . . 85
3.5.4 Quality Control. 88
3.6 Summary. 89
Questions and Problems. 89
4 Numerical Summary Measures. 95
4.1 Introduction. 96
4.2 Measures of Central Tendency. 96
4.2.1 The Arithmetic Mean. 97
4.2.2 The Geometric Mean. 98
4.2.3 The Median. 99
4.2.4 The Mode. 101
4.3 Measures of Dispersion. 102
4.3.1 The Variance and the Standard Deviation. 102
4.3.2 The Mean Absolute Deviation. 105
4.3.3 The Range. 107
4.3.4 The Coefficient of Variation. 107
4.4 Measures of Relative Position. 109
4.4.1 Percentiles, Quartiles, and Interquartile Range. 109
4.4.2 Box and Whisker Plots: Graphical Descriptions
Based on Quartiles. Ill
4.4.3 Z Scores. 112
4.5 Measures of Shape. 113
4.5.1 Skewness. 113
4.5.2 Kurtosis. 116
4.6 Calculating Certain Summary Measures from
Grouped Data (Optional). 117
4.6.1 The Mean. 117
4.6.2 The Median. 119
4.6.3 The Mode. 119
4.6.4 Variance and Standard Deviation. 120
4.6.5 Percentiles. 120
4.7 Applications. 122
4.8 Summary. 129
Questions and Problems. 129
Project I: Project for Descriptive Statistics. 146
Appendix 1: Shortcut Formulas for Calculating Variance
and Standard Deviation. 147
Appendix 2: Shortcut Formulas for Calculating Group
Variance and Standard Deviation. 148
Appendix 3: Financial Ratio Analysis for Two
Pharmaceutical Firms. 148
part II Probability and Important Distributions
c probability Concepts and Their Analysis. 157
5.1 Introduction. 158
5.2 Random Experiment. Outcomes, Sample Space, Event,
and Probability. 158
5.2.1 Properties of Random Experiments. 159
5.2.2 Sample Space of an Experiment and the
Venn Diagram. 159
5.2.3 Probabilities of Outcomes. 161
5.2.4 Subjective Probability. 165
5.3 Alternative Events and Their Probabilities. 166
5.3.1 Probabilities of Union and Intersection of Events. 166
5.3.2 Partitions, Complements, and Probability
of Complements. 171
5.3.3 Using Combinatorial Mathematics to Determine
the Number of Simple Events. 173
5.4 Conditional Probability and Its Implications. 174
5.4.1 Basic Concept of Conditional Probability. 174
5.4.2 Multiplication Rule of Probability . . 176
5.5 Joint Probability and Marginal Probability. 177
5.5.1 Joint Probability. 177
5.5.2 Marginal Probabilities. 179
5.6 Independent, Dependent, and Mutually Exclusive Events. 182
5.7 Bayes’Theorem. 183
5.8 Business Applications. 185
5.9 Summary. 193
Questions and Problems. 193
Appendix 1: Permutations and Combinations. 204
6 Discrete Random Variables and Probability Distributions. 211
6.1 Introduction. 212
6.2 Discrete and Continuous Random Variables. 212
6.3 Probability Distributions for Discrete Random Variables. 213
6.3.1 Probability Distribution. 213
6.3.2 Probability Function and Cumulative
Distribution Function. 216
6.4 Expected Value and Variance for Discrete
Random Variables. 217
6.5 The Bernoulli Process and the Binomial
Probability Distribution. . 221
6.5.1 The Bernoulli Process. 221
6.5.2 Binomial Distribution. 222
6.5.3 Probability Function. 224
6.5.4 Mean and Variance. 228
6.6 The Hypergeometric Distribution (Optional). 229
6.6.1 The Hypergeometric Formula. 230
6.6.2 Mean and Variance. 231
6.7 The Poisson Distribution and Its Approximation
to the Binomial Distribution. 232
6.7.1 The Poisson Distribution. 233
6.7.2 The Poisson Approximation to the
Binomial Distribution. 235
6.8 Jointly Distributed Discrete Random Variables (Optional). 237
6.8.1 Joint Probability Function. 237
6.8.2 Marginal Probability Function. 238
6.8.3 Conditional Probability Function. 239
6.8.4 Independence. 240
6.9 Expected Value and Variance of the Sum
of Random Variables (Optional). 242
6.9.1 Covariance and Coefficient of Correlation
Between Two Random Variables. 242
6.9.2 Expected Value and Variance of the Summation
of Random Variables X and Y. 244
6.9.3 Expected Value and Variance of Sums
of Random Variables. 247
6.10 Summary. 250
Questions and Problems. 250
Appendix 1: The Mean and Variance of the
Binomial Distribution. 259
Appendix 2: Applications of the Binomial Distribution
to Evaluate Call Options. 260
The Normal and Lognormal Distributions. 271
7.1 Introduction. 271
7.2 Probability Distributions for Continuous
Random Variables. 272
7.2.1 Continuous Random Variables. 272
7.2.2 Probability Distribution Functions for Discrete
and Continuous Random Variables. 273
7.3 The Normal and Standard Normal Distribution. 278
7.3.1 The Normal Distribution. 278
7.3.2 Areas Under the Normal Curve. 279
7.3.3 How to Use the Normal Area Table. 282
7.4 The Lognormal Distribution and Its Relationship
to the Normal Distribution (Optional). 286
7.4.1 The Lognormal Distribution. 286
7.4.2 Mean and Variance of Lognormal Distribution. 286
7.5 The Normal Distribution as an Approximation
to the Binomial and Poisson Distributions. 290
7.5.1 Normal Approximation to the
Binomial Distribution. 290
7.5.2 Normal Approximation to the
Poisson Distribution. 292
7.6 Business Applications. 293
7.7 Summary. 303
Questions and Problems. 304
Appendix 1: Mean and Variance for Continuous
Random V ari able s. 315
Appendix 2: Cumulative Normal Distribution Function
and the Option Pricing Model. 321
Appendix 3: Lognormal Distribution Approach to Derive
the Option Pricing Model. 326
8 Sampling and Sampling Distributions. 331
8.1 Introduction. 331
8.2 Sampling from a Population. 332
8.2.1 Sampling Error and Nonsampling Error. 333
8.2.2 Selection of a Random Sample. 334
8.3 Sampling Cost Versus Sampling Error. 337
8.3.1 Sampling Size and Accuracy. 338
8.3.2 Time Constraints. 339
8.4 Sampling Distribution of the Sample Mean. 339
8.4.1 All Possible Random Samples and Their Mean. 340
8.4.2 Mean and Variance for a Sample Mean. 345
8.4.3 Sample Without Replacement from
a Finite Sample. 346
8.5 Sampling Distribution of the Sample Proportion. 352
8.6 The Central Limit Theorem. 354
8.7 Other Business Applications. 357
8.8 Summary. 360
Questions and Problems. 360
Appendix 1: Sampling Distribution from a Uniform
Population Distribution. 373
9 Other Continuous Distributions and Moments
for Distributions. 381
9.1 Introduction. 382
9.2 The Uniform Distribution. 382
9.3 Student’s t Distribution. 385
9.4 The Chi-Square Distribution and the Distribution
of Sample Variance. 388
9.4.1 The Chi-Square Distribution. 388
9.4.2 The Distribution of Sample Variance. 392
9.5 The F Distribution. 393
9.6 The Exponential Distribution (Optional). 396
9.7 Moments and Distributions (Optional). 398
9.7.1 The Second Moment and the Coefficient
of Variation. 398
9.7.2 The Third Moment and the Coefficient
of Skewness. 399
9.7.3 Kurtosis and the Coefficient of Kurtosis. 401
9.7.4 Skewness and Kurtosis for Normal
and Lognormal Distributions. 401
9.8 Analyzing the First Four Moments of Rates of Return
of the 30 DJI Firms. 403
9.9 Summary. 405
Questions and Problems. 405
Project II: Project for Probability and Important Distributions. 412
Appendix 1: Derivation of the Mean and Variance
for a Uniform Distribution. 413
Appendix 2: Derivation of the Exponential Density Function. 415
Appendix 3: The Relationship Between the Moment
About the Origin and the Moment About the Mean. 418
Appendix 4: Derivations of Mean, Variance, Skewness,
and Kurtosis for the Lognormal Distribution. 418
Appendix 5: Noncentral x and the Option Pricing Model. 420
Part III Statistical Inferences Based on Samples
10 Estimation and Statistical Quality Control. 425
10.1 Introduction. 426
10.2 Point Estimation. 426
10.2.1 Point Estimate, Estimator, and Estimation. 426
10.2.2 Four Important Properties of Estimators. 428
10.2.3 Mean Squared Error for Choosing
Point Estimator. 432
10.3 Interval Estimation. 433
10.4 Interval Estimates for pi When ox Is Known. 434
10.5 Confidence Intervals for pi When Is Unknown. 440
10.6 Confidence Intervals for the Population Proportion. 445
10.7 Confidence Intervals for the Variance. 447
10.8 An Overview of Statistical Quality Control. 449
10.8.1 The Sample Size of an Inspection. 450
10.8.2 Acceptance Sampling and Its
Alternative Plans. 450
10.8.3 Process Control. 452
10.9 Control Charts for Quality Control. 452
10.9.1 X -Chart. . 453
10.9.2 R -Chart and 5-Chart. 456
10.9.3 Control Charts for Proportions. 462
10.10 Further Applications. 464
10.11 Summary. 468
Questions and Problems. . 468
Appendix 1: Control Chart Approach for Cash Management. 480
Appendix 2: Using MINTTAB to Generate Control Charts. 483
11 Hypothesis Testing. 487
11.1 Introduction. 488
11.2 Concepts and Errors of Hypothesis Testing. 488
11.2.1 Concepts. 488
11.2.2 Type I and Type II Errors. 490
11.3 Hypothesis Test Construction and Testing Procedure. 490
11.3.1 Two Types of Hypothesis Tests. 490
11.3.2 The Trade-off Between Type I
and Type II Errors. 493
11.3.3 The P-Value Approach to Hypothesis Testing. 495
11.4 One-Tailed Tests of Means for Large Samples. 496
11.4.1 One-Sample Tests of Means. 496
11.4.2 The za-Value Approach. 498
11.4.3 The xa -Value Approach. 499
11.4.4 The p- Value Approach. 499
11.4.5 Two-Samples Tests of Means. 500
11.5 Two-Tailed Tests of Means for Large Samples. 504
11.5.1 One-Sample Tests of Means. 504
11.5.2 Confidence Intervals and Hypothesis Testing. 506
11.5.3 Two-Samples Tests of Means. 507
11.6 Small-Sample Tests of Means with Unknown Population
Standard Deviations. 509
11.6.1 One-Sample Tests of Means. 509
11.6.2 Two-Samples Tests of Means. 510
11.7 Hypothesis Testing for a Population Proportion. 513
11.8 Chi-Square Tests of the Variance
of a Normal Distribution. 516
11.9 Comparing the Variances of Two Normal Populations. 518
11.10 Business Applications. 518
11.11 Summary. 523
Questions and Problems. 524
Appendix 1: The Power of a Test, the Power Function,
and the Operating-Characteristic Curve. 536
12 Analysis of Variance and Chi-Square Tests. 543
12.1 Introduction. 544
12.2 One-Way Analysis of Variance. 544
12.2.1 Defining One-Way ANOVA. 545
12.2.2 Specifying the Hypotheses. 545
12.2.3 Generalizing the One-Way ANOVA. 546
12.2.4 Between-Treatments and Within-Treatment
Sums of Squares. 548
12.2.5 Between-Treatments and Within-Treatment
Mean Squares. 551
12.2.6 The Test Statistic. 552
12.2.7 Population Model for One-Way ANOVA. 553
12.3 Simple and Simultaneous Confidence Intervals. 554
12.3.1 Simple Comparison. 554
12.3.2 Scheffe’s Multiple Comparison . 556
12.4 Two-Way ANOVA with One Observation
in Each Cell, Randomized Blocks. 557
12.4.1 Basic Concept. 557
12.4.2 Specifying the Hypotheses. 558
12.4.3 Between and Residual Sum of Squares. 558
12.4.4 Between Variance, Error Variance,
and F-Test. 560
12.4.5 Population Model for Two-Way ANOVA
with One Observation in Each Cell. 561
12.5 Two-Way ANOVA with More than One
Observation in Each Cell. 563
12.5.1 Basic Concept and Hypothesis Testing. 563
12.5.2 Generalizing the Two-Way ANOVA. 566
12.6 Chi-Square as a Test of Goodness of Fit. 568
12.7 Chi-Square as a Test of Independence. 572
12.8 Business Applications. 574
12.9 Summary. 582
Questions and Problems . . 582
Project III: Project for Statistical Inferences Based on Samples. 606
Appendix 1: ANOVA and Statistical Quality Control. 607
Part IV Regression and Correlation: Relating Two or More Variables
13 Simple Linear Regression and the Correlation Coefficient. 615
13.1 Introduction. 616
13.2 Population Parameters and the Regression Models. 616
13.2.1 Data Description. 617
13.2.2 Building the Population Regression Model. 618
13.2.3 Sample Versus Population Regression Model. 621
13.3 The Least-Squares Estimation of a and ¡3. 622
13.3.1 Scatter Diagram. 622
13.3.2 The Method of Least Squares. 624
13.3.3 Estimation of Intercept and Slope. 625
13.4 Standard Assumptions for Linear Regression. 629
13.5 The Standard Error of Estimate and the Coefficient
of Determination. 631
13.5.1 Variance Decomposition. 632
13.5.2 Standard Error of Residuals (Estimate). 635
13.5.3 The Coefficient of Determination. 635
13.6 The Bivariate Normal Distribution
and Correlation Analysis. 636
13.6.1 The Sample Correlation Coefficient. 638
13.6.2 The Relationship Between r and b. 639
13.6.3 The Relationship Between r and R2. 639
13.7 Summary. 646
Questions and Problems. 646
Appendix 1: Derivation of Normal Equations and Optimal
Portfolio Weights. 659
Appendix 2: The Derivation of Equation 13.20. 661
Appendix 3: The Bivariate Normal Density Function. 661
Appendix 4: American Call Option and the Bivariate
Normal CDF. 664
14 Simple Linear Regression and Correlation: Analyses
and Applications. 675
14.1 Introduction. 675
14.2 Tests of the Significance of a and ¡3. 676
14.2.1 Hypothesis Testing and Confidence Interval
for ¡3 and a. 677
14.2.2 The F-Test Versus the r-Test. 682
14.3 Test of the Significance of p. 685
14.3.1 r-Test for Testing p — 0. 686
14.3.2 z-Test for Testing p = 0 or p = Constant. 687
14.4 Confidence Interval for the Mean Response
and Prediction Interval for the Individual Response. 688
14.4.1 Point Estimates of the Mean Response
and the Individual Response. 688
14.4.2 Interval Estimates of Forecasts under Three
Cases of Estimated Variance. 689
14.4.3 Calculating Standard Errors. 691
14.4.4 Confidence Interval for the Mean Response and
Prediction Interval for the Individual Response. 693
14.4.5 Using MINITAB to Calculate Confidence
Interval and Interval. 696
14.5 Business Applications. 700
14.6 Using Computer Programs to Do Simple
Regression Analysis. 713
14.7 Summary. 714
Questions and Problems. 717
Appendix 1 : Impact of Measurement Error and Proxy
Error on Slope Estimates. 734
Appendix 2: The Relationship Between the E-Test
and the r-Test. 736
Appendix 3: Derivation of Variance for Alternative Forecasts. 736
15 Multiple Linear Regression. 739
15.1 Introduction. 740
15.2 The Model and Its Assumptions. 740
15.2.1 The Multiple Regression Model. 740
15.2.2 The Regression Plane for Two
Explanatory Variables. 741
15.2.3 Assumptions for the Multiple Regression Model. 742
15.3 Estimating Multiple kegression Parameters. 744
15.4 The Residual Standard Error and the Coefficient
of Determination. 747
15.4.1 The Residual Standard Error. 747
15.4.2 The Coefficient of Determination. 748
15.5 Tests on Sets and Individual Regression Coefficients. 750
15.5.1 Test on Sets of Regression Coefficients. 750
15.5.2 Hypothesis Tests for Individual
Regression Coefficients. 752
15.6 Confidence Interval for the Mean Response and
Prediction Interval for the Individual Response. 756
15.6.1 Point Estimates of the Mean and the
Individual Responses. 756
15.6.2 Interval Estimates of Forecasts. 756
15.7 Business and Economic Applications. 759
15.8 Using Computer Programs to Do Multiple
Regression Analyses. 766
15.8.1 SAS Program for Multiple Regression Analysis . . . . 766
15.8.2 MINITAB Program for Multiple
Regression Prediction. 771
15.8.3 Stepwise Regression Analysis. 772
15.9 Summary. 776
Questions and Problems. Ill
Appendix 1: Derivation of the Sampling Variance
of the Least-Squares Slope Estimations. 788
Appendix 2: Derivation of Equation 15.30. 791
16 Other Topics in Applied Regression Analysis. 793
16.1 Introduction. 794
16.2 Multicollinearity. 794
16.2.1 Definition and Effect. 794
16.2.2 Rules of Thumb in Determining the Degree
of Collinearity. 796
16.3 Heteroscedasticity. 798
16.3.1 Definition and Concept. 798
16.3.2 Evaluating the Existence
of Heteroscedasticity. 800
16.4 Autocorrelation. 804
16.4.1 Basic Concept. 804
16.4.2 The Durbin-Watson Statistic. 805
16.5 Model Specification and Specification
Bias (Optional). 810
16.6 Nonlinear Models (Optional). 816
16.6.1 The Quadratic Model. 816
16.6.2 The Log-Linear and the Log-Log-Linear
Model. 819
16.7 Lagged Dependent Variables (Optional). 822
16.8 Dummy Variables. 832
16.9 Regression with Interaction Variables. 837
16.10 Regression Approach to Investigating the Effect
of Alternative Business Strategies. 840
16.11 Summary. 841
Questions and Problems. 841
Project IV: Project for Regression and Correlation Analyses. 859
Appendix 1: Dynamic Ratio Analysis. 869
Appendix 2: Term Structure of Interest Rate. 870
Part V Selected Topics in Statistical Analysis for Business and Economics
17 Nonparametric Statistics. 877
17.1 Introduction. 878
17.2 The Matched-Pairs Sign Test. 879
17.3 The Wilcoxon Matched-Pairs Signed-Rank Test. 881
17.4 Mann-Whitney U Test (Wilcoxon Rank-Sum Test). 884
17.5 Kruskal-Wallis Test for m Independent Samples. 889
17.6 Spearman Rank Correlation Test. 892
17.7 The Number-of-Runs Test. 894
17.8 Business Applications. 896
17.9 Summary. 905
Questions and Problems. 905
18 Time Series: Analysis, Model, and Forecasting. 927
18.1 Introduction. 928
18.2 The Classical Time-Series Component Model. 928
18.2.1 The Trend Component. 929
18.2.2 The Seasonal Component. 929
18.2.3 The Cyclical Component and Business Cycles. 929
18.2.4 The Irregular Component. 932
18.3 Moving Average and Seasonally Adjusted Time Series. 934
18.3.1 Moving Averages. 934
18.3.2 Seasonal Index and Seasonally Adjusted
Time Series. 935
18.4 Linear and Log-Linear Time Trend Regressions. 941
18.5 Exponential Smoothing and Forecasting. 943
18.5.1 Simple Exponential Smoothing and Forecasting . . . . 943
18.5.2 The Holt-Winters Forecasting Model for
Nonseasonal Series. 947
18.6 Autoregressive Forecasting Model. 952
18.7 Summary. 956
Questions and Problems. 956
Appendix 1 : The Holt—Winters Forecasting Model
for Seasonal Series. 968
19 Index Numbers and Stock Market Indexes. 973
19.1 Introduction. 974
19.2 Price Indexes. 974
19.2.1 Simple Aggregative Price Index. 974
19.2.2 Simple Average of Price Relatives. 976
19.2.3 Weighted Relative Price Index. 977
19.2.4 Weighted Aggregative Price Index. 979
19.3 Quantity Indexes. 982
19.3.1 Laspeyres Quantity Index. 982
19.3.2 Paasche Quantity Index. 983
19.3.3 Fisher’s Ideal Quantity Index. 985
19.3.4 FRB Index of Industrial Production. 985
19.4 Value Index. 986
19.5 Stock Market Indexes. 986
19.5.1 Market-Value-Weighted Index. 987
19.5.2 Price-Weighted Index. 988
19.5.3 Equally Weighted Index. 990
19.5.4 Wilshire 5000 Equity Index. 991
19.6 Business and Economic Applications. 993
19.7 Summary. 1002
Questions and Problems. 1002
Appendix 1: Options on Stock Indices and Currencies. 1013
Appendix 2: Index Futures and Hedge Ratio. 1016
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20 Sampling Surveys: Methods and Applications.
20.1 Introduction.
20.2 Sampling and Nonsampling Errors.
20.3 Simple and Stratified Random Sampling.
20.3.1 Designing the Sampling Study.
20.3.2 Statistical Inferences in Terms of Simple
Random Sampling.
20.3.3 Stratified Random Sampling.
20.4 Determining the Sample Size.
20.4.1 Sample Size for Simple Random Sampling.
20.4.2 Sample Size for Stratified Random Sampling.
20.5 Two-Stage Cluster Sampling.
20.6 Ratio Estimates Versus Regression Estimates.
20.6.1 Ratio Method.
20.6.2 Regression Method.
20.6.3 Comparison of the Ratio and Regression Methods . . .
20.7 Business and Economic Applications.
20.8 Summary.
Questions and Problems.
Appendix 1: The Jackknife Method for Removing Bias
from a Sample Estimate.
21 Statistical Decision Theory: Methods and Applications.
21.1 Introduction.
21.2 Four Key Elements of a Decision.
21.3 Decisions Based on Extreme Values.
21.3.1 Maxim in Criterion.
21.3.2 Minimax Regret Criterion.
21.4 Expected Monetary Value and Utility Analysis.
21.4.1 The Expected Monetary Value Criterion.
21.4.2 Utility Analysis.
21.5 Bayes’ Strategies.
21.6 Decision Trees and Expected Monetary Values.
21.7 Mean and Variance Trade-Off Analysis.
21.7.1 The Mean-Variance Rule and the
Dominance Principle.
21.7.2 The Capital Market Line.
21.7.3 The Capital Asset Pricing Model.
21.8 The Mean and Variance Method for Capital
Budgeting Decisions.
21.8.1 Statistical Distribution of Cash Flow.
21.9 Summary.
Questions and Problems.
Project V: Project for Selected Topics in Statistical Analysis.
Appendix 1: Using the Spreadsheet in Decision-Tree Analysis. 1116
Appendix 2: Graphical Derivation of the Capital Market Line. 1119
Appendix 3: Present Value and Net Present Value. 1121
Appendix 4: Derivation of Standard Deviation for NPV. 1123
Appendix A Statistical Tables. 1125
Table A. 1 Probability function of the binomial distribution. 1125
Table A.2 Poisson probabilities. 1130
Table A.3 The standardized normal distribution. 1135
Table A.4 Critical values oft. 1137
Table A.5 Critical values of . 1138
Table A.6 Critical values of F. 1140
Table A.7 Exponential function. 1147
Table A.8 Random numbers. 1148
Table A.9 Cutoff points for the distribution of the Durbin-Watson
test statistics. 1149
Table A.10 Lower and upper critical values R for the runs test. 1152
Table A.l 1 Critical values of W in the Wilcoxon Matched-Pairs
Signed-Rank test. 1153
Table A. 12 Lower and upper critical values and R,n
of the Wilcoxon Rank-Sum test. 1153
Table A. 13 Factors for control chart. 1154
Table A.14 Present value of $1. 1155
Appendix B Description of Data Sets. 1157
Appendix C Introduction to MINITAB 16. 1161
Appendix D Introduction to SAS: Microcomputer Version. 1165
Appendix E Useful Formulas in Statistics. 1171
Appendix F Important Finance and Accounting Topics. 1193
Index. 1195
is the definitive Business Statistics book to use Finance, Economics, and Accounting data throughout the entire book. Therefore, this book gives students an understanding of how to apply the methodology of statistics to real world situations. In particular, this book shows how
statistical inference, regression methods, and statistical decision theory can be used to analyze individual stock price, stock index, stock rate of return, market rate of return, and decision making. In addition, this book also shows how time-series analysis and the statistical decision theory method can be used to analyze accounting and financial data. In this fully-revised edition, the real world examples have been reconfigured and sections have been edited for better |
| any_adam_object | 1 |
| author | Lee, Cheng F. Lee, John C. Lee, Alice C. |
| author_GND | (DE-588)129807907 (DE-588)132014335 |
| author_facet | Lee, Cheng F. Lee, John C. Lee, Alice C. |
| author_role | aut aut aut |
| author_sort | Lee, Cheng F. |
| author_variant | c f l cf cfl j c l jc jcl a c l ac acl |
| building | Verbundindex |
| bvnumber | BV041213837 |
| callnumber-first | H - Social Science |
| callnumber-label | HF1017 |
| callnumber-raw | HF1017.L42 1993 |
| callnumber-search | HF1017.L42 1993 |
| callnumber-sort | HF 41017 L42 41993 |
| callnumber-subject | HF - Commerce |
| classification_rvk | QH 240 |
| ctrlnum | (OCoLC)843459927 (DE-599)BSZ381141535 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 3. ed. |
| format | Book |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
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| id | DE-604.BV041213837 |
| illustrated | Illustrated |
| indexdate | 2024-08-28T00:11:07Z |
| institution | BVB |
| isbn | 9781461458968 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026188509 |
| oclc_num | 843459927 |
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| physical | XLVIII, 1206 S. graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
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| publisher | Springer |
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| spelling | Lee, Cheng F. Verfasser (DE-588)129807907 aut Statistics for business and financial economics Cheng-Few Lee ; John C. Lee ; Alice C. Lee 3. ed. New York [u.a.] Springer 2013 XLVIII, 1206 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Commercial statistics Finance / Statistical methods Wirtschaftsstatistik (DE-588)4066517-3 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Wirtschaftsstatistik (DE-588)4066517-3 s b DE-604 Lee, John C. Verfasser aut Lee, Alice C. Verfasser (DE-588)132014335 aut Erscheint auch als Online-Ausgabe 978-1-4614-5897-5 Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188509&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188509&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Lee, Cheng F. Lee, John C. Lee, Alice C. Statistics for business and financial economics Commercial statistics Finance / Statistical methods Wirtschaftsstatistik (DE-588)4066517-3 gnd |
| subject_GND | (DE-588)4066517-3 (DE-588)4123623-3 |
| title | Statistics for business and financial economics |
| title_auth | Statistics for business and financial economics |
| title_exact_search | Statistics for business and financial economics |
| title_full | Statistics for business and financial economics Cheng-Few Lee ; John C. Lee ; Alice C. Lee |
| title_fullStr | Statistics for business and financial economics Cheng-Few Lee ; John C. Lee ; Alice C. Lee |
| title_full_unstemmed | Statistics for business and financial economics Cheng-Few Lee ; John C. Lee ; Alice C. Lee |
| title_short | Statistics for business and financial economics |
| title_sort | statistics for business and financial economics |
| topic | Commercial statistics Finance / Statistical methods Wirtschaftsstatistik (DE-588)4066517-3 gnd |
| topic_facet | Commercial statistics Finance / Statistical methods Wirtschaftsstatistik Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188509&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026188509&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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