Probability and statistics with R:
Gespeichert in:
Hauptverfasser: | , , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Boca Raton, Fla.
CRC Press
[2016]
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Ausgabe: | Second editon |
Schriftenreihe: | A Chapman & Hall book
|
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | XXXIII, 949 Seiten Illustrationen |
ISBN: | 9781466504394 |
Internformat
MARC
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035 | |a (DE-599)BVBBV042926314 | ||
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100 | 1 | |a Ugarte, María Dolores |e Verfasser |0 (DE-588)1115277138 |4 aut | |
245 | 1 | 0 | |a Probability and statistics with R |c María Dolores Ugarte ; Ana F. Militino ; Alan T. Arnholt |
250 | |a Second editon | ||
264 | 1 | |a Boca Raton, Fla. |b CRC Press |c [2016] | |
264 | 4 | |c 2016 | |
300 | |a XXXIII, 949 Seiten |b Illustrationen | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 0 | |a A Chapman & Hall book | |
650 | 4 | |a Datenverarbeitung | |
650 | 4 | |a R (Computer program language) | |
650 | 4 | |a Probabilities |x Data processing | |
650 | 4 | |a Mathematical statistics |x Data processing | |
650 | 4 | |a S (Computer system) | |
650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Wahrscheinlichkeitsrechnung |0 (DE-588)4064324-4 |2 gnd |9 rswk-swf |
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689 | 0 | 1 | |a Wahrscheinlichkeitsrechnung |0 (DE-588)4064324-4 |D s |
689 | 0 | 2 | |a R |g Programm |0 (DE-588)4705956-4 |D s |
689 | 0 | |C b |5 DE-604 | |
700 | 1 | |a Militino, Ana F. |e Verfasser |0 (DE-588)1115277596 |4 aut | |
700 | 1 | |a Arnholt, Alan T. |e Verfasser |0 (DE-588)1115277707 |4 aut | |
856 | 4 | 2 | |m Digitalisierung UB Passau - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028353500&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
Datensatz im Suchindex
_version_ | 1805075531964612608 |
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adam_text |
Contents
List of Figures xv
List of Tables xxv
Preface to the Second Edition xxix
Preface to the First Edition xxxi
1 What Is R? 1
1.1 Introduction to R. 1
1.2 Downloading and Installing R. 1
1.2.1 Installing R under Windows . 2
1.2.2 Launching R. 4
1.2.3 A First Look at R (Interactive Mode). 4
1.3 Vectors . 6
1.3.1 Naming Cautions . 10
1.3.2 Vector Indexing. 10
1.3.3 Generating Vector Sequences and Repeating Vector Constants . . 11
1.3.4 Filtering Vectors. 12
1.4 Mode and Class of an Object . 13
1.5 Getting Help . 14
1.6 External Editors . 15
1.7 RStudio . 16
1.8 Packages. 19
1.9 R Data Structures . 21
1.9.1 Arrays and Matrices. 21
1.9.2 Vector and Matrix Operations. 27
1.9.3 Factors. 28
1.9.4 Lists. 29
1.9.5 Data Frames. 31
1.9.5.1 Creating Data Frames. 32
1.9.5.2 Accessing Data Frames. 33
1.9.5.3 Accessing Data from Packages. 37
1.10 Reading and Saving Data in R . 39
1.10.1 Using read, table О . 40
1.10.2 Using download.file() 41
1.10.3 Reading Data from Secure Websites. 42
1.10.4 Using scanO. 44
1.10.5 Reading Excel (.xlsx) Files. 45
1.10.6 Saving Data Frames to External Files. 47
1.11 Working with Data. 47
1.11.1 Dealing with M Values. 51
1.11.2 Creating New Variables in a Data Frame. 54
v
vi Contents
1.11.3 Sorting a Data Frame by One or More of Its Columns. 55
1.11.4 Merging Data Frames. 56
1.12 Using Logical Operators with Data Frames . 58
1.13 Tables . 62
1.14 Summarizing Functions . 66
1.15 Probability Functions . 68
1.16 Flow Control . 69
1.17 Creating Functions. 74
1.18 Simple Imputation . 78
1.19 Using plotQ . 80
1.20 Coordinate Systems and Traditional Graphic’s States . 85
1.21 Problems . 91
2 Exploring Data 97
2.1 What Is Statistics?. 97
2.2 Data. 97
2.3 Displaying Qualitative Data. 98
2.3.1 Tables. 98
2.3.2 Barplots . 100
2.3.3 Dot Charts. 100
2.3.4 Pie Charts. 103
2.4 Displaying Quantitative Data. 104
2.4.1 Stem-and-Leaf Plots. 104
2.4.2 Strip Charts. 105
2.4.3 Density Curves for Exploring Univariate Data. 107
2.4.3.1 Histograms. 107
2.4.3.2 Kernel Density Estimators. 114
2.5 Summary Measures of Location. 120
2.5.1 The Mean . 120
2.5.2 The Median . 121
2.5.3 Mode. 123
2.5.4 Quantiles. 124
2.5.5 Hinges and the Five-Number Summary. 126
2.5.6 Boxplots. 127
2.6 Summary Measures of Spread. 129
2.6.1 Range. 130
2.6.2 Interquartile Range. 130
2.6.3 Variance . 131
2.6.4 Sample Coefficient of Variation. 132
2.6.5 The Median Absolute Deviation (MAD) . 133
2.7 Bivariate Data . 134
2.7.1 Two-Way Contingency Tables. 134
2.7.2 Graphical Representations of Two-Way Contingency Tables . 136
2.7.3 Comparing Samples. 138
2.7.4 Relationships between Two Numeric Variables. 143
2.7.5 Correlation. 144
2.7.6 Fitting Lines to Bivariate Data. 147
2.8 Complex Plot Arrangements . 151
2.9 Multivariate Data . 154
2.9.1 Graphs for Categorical Data. 156
2.9.2 Lattice Graphs. 162
Contents
vii
2.9.3 Arranging Several Lattice Graphs on a Single Page . 165
2.9.4 Panel Functions. 167
2.9.5 Graphics with ggplot2. 169
2.9.5.1 Shading a Region of a Density Curve . 177
2.9.5.2 Violin Plots. 180
2.9.5.3 Adding a Smoothed Line. 184
2.9.5.4 Choropleth Maps. 188
2.9.6 Arranging Several ggplot Graphs on a Single Page. 191
2.10 Problems . 193
3 General Probability and Random Variables 199
3.1 Introduction. 199
3.2 Counting Techniques. 199
3.2.1 Sampling with Replacement . 199
3.2.2 Sampling without Replacement. 200
3.2.3 Combinations . 201
3.3 Axiomatic Probability . 202
3.3.1 Sample Space and Events. 203
3.3.2 Set Theory. 203
3.3.3 Interpreting Probability. 204
3.3.3.1 Relative Frequency Approach to Probability . 204
3.3.3.2 Axiomatic Approach to Probability . 205
3.3.4 Conditional Probability. 208
3.3.5 The Law of Total Probability and Bayes’ Rule. 210
3.3.6 Independent Events. 213
3.4 Random Variables . 214
3.4.1 Discrete Random Variables. 215
3.4.1.1 Mode, Median, and Percentiles. 217
3.4.1.2 Expected Values. 217
3.4.1.3 Moments. 219
3.4.2 Continuous Random Variables. 222
3.4.2.1 Numerical Integration with R. 225
3.4.2.2 Mode, Median, and Percentiles. 226
3.4.2.3 Expected Values. 229
3.4.3 Markov’s Theorem and Chebyshev’s Inequality. 231
3.4.4 Weak Law of Large Numbers. 233
3.4.5 Skewness. 234
3.5 Moment Generating Functions . 235
3.6 Problems . 238
4 Univariate Probability Distributions 249
4.1 Introduction. 249
4.2 Discrete Univariate Distributions. 249
4.2.1 Discrete Uniform Distribution. 249
4.2.2 Bernoulli and Binomial Distributions. 250
4.2.3 Poisson Distribution. 256
4.2.4 Geometric Distribution. 263
4.2.5 Negative Binomial Distribution. 266
4.2.6 Hypergeometric Distribution. 269
4.3 Continuous Univariate Distributions . 271
4.3.1 Uniform Distribution (Continuous) . 272
viii Contents
4.3.2 Exponential Distribution. 276
4.3.3 Gamma Distribution . 282
4.3.4 Hazard Function, Reliability Function, and Failure Rate. 286
4.3.5 Weibull Distribution. 291
4.3.6 Beta Distribution. 293
4.3.7 Normal (Gaussian) Distribution. 296
4.4 Problems . 307
5 Multivariate Probability Distributions 315
5.1 Joint Distribution of Two Random Variables . 315
5.1.1 Joint pdf for Two Discrete Random Variables. 315
5.1.2 Joint pdf for Two Continuous Random Variables. 317
5.2 Independent Random Variables. 319
5.3 Several Random Variables. 319
5.4 Conditional Distributions . 322
5.5 Expected Values, Covariance, and Correlation. 326
5.5.1 Expected Values. 326
5.5.2 Covariance. 327
5.5.3 Correlation. 330
5.6 Multinomial Distribution . 332
5.7 Bivariate Normal Distribution. 333
5.8 Problems . 342
6 Sampling and Sampling Distributions 351
6.1 Sampling . 351
6.1.1 Simple Random Sampling. 352
6.1.2 Stratified Sampling. 354
6.1.3 Systematic Sampling . 355
6.1.4 Cluster Sampling . 355
6.2 Parameters . 356
6.2.1 Infinite Populations’ Parameters. 356
6.2.2 Finite Populations’ Parameters. 357
6.3 Estimators . 357
6.3.1 Plug-In Principle. 359
6.4 Sampling Distribution of the Sample Mean . 359
6.5 Sampling Distribution for a Statistic from an Infinite Population . 367
6.5.1 Sampling Distribution for the Sample Mean. 367
6.5.1.1 First Case: Sampling Distribution of X When Sampling
from a Normal Distribution. 368
6.5.1.2 Second Case: Sampling Distribution of X When X Is
Not a Normal Random Variable. 370
6.5.2 Sampling Distribution for X—Y When Sampling from Two Independent
Normal Populations. 375
6.5.3 Sampling Distribution for the Sample Proportion . 377
6.5.4 Expected Value and Variance of the Uncorrected Sample Variance
and the Sample Variance. 382
6.6 Sampling Distributions Associated with the Normal Distribution . 383
6.6.1 Chi-Square Distribution (x2). 383
6.6.1.1 The Relationship between the x2 Distribution and the
Normal Distribution. 386
Contents ix
6.6.1.2 Sampling Distribution for and S2 When Sampling
from Normal Populations. 389
6.6.2 ¿-Distribution . 394
6.6.3 The F Distribution. 397
6.7 Problems . 400
7 Point Estimation 405
7.1 Introduction. 405
7.2 Properties of Point Estimators . 405
7.2.1 Mean Square Error . 405
7.2.2 Unbiased Estimators. 406
7.2.3 Efficiency. 409
7.2.3.1 Relative Efficiency. 410
7.2.4 Consistent Estimators. 414
7.2.5 Robust Estimators. 415
7.3 Point Estimation Techniques . 416
7.3.1 Method of Moments Estimators. 417
7.3.2 Likelihood and Maximum Likelihood Estimators. 419
7.3.2.1 Fisher Information. 431
7.3.2.2 Fisher Information for Several Parameters. 433
7.3.2.3 Properties of Maximum Likelihood Estimators. 435
7.3.2.4 Finding Maximum Likelihood Estimators for Multiple
Parameters. 440
7.3.2.5 Multi-Parameter Properties of MLEs . 442
7.4 Problems . 444
8 Confidence Intervals 453
8.1 Introduction. 453
8.2 Confidence Intervals for Population Means. 454
8.2.1 Confidence Interval for the Population Mean When Sampling from
a Normal Distribution with Known Population Variance. 454
8.2.1.1 Determining Required Sample Size. 460
8.2.2 Confidence Interval for the Population Mean When Sampling from
a Normal Distribution with Unknown Population Variance . 464
8.2.3 Confidence Interval for the Difference in Population Means When
Sampling from Independent Normal Distributions with Known
Equal Variances. 466
8.2.4 Confidence Interval for the Difference in Population Means When
Sampling from Independent Normal Distributions with Known but
Unequal Variances. 470
8.2.5 Confidence Interval for the Difference in IVfeans When Sampling
from Independent Normal Distributions with Variances That Are
Unknown but Assumed Equal .,. 474
8.2.6 Confidence Interval for a Difference in Means When Sampling
from Independent Normal Distributions with Variances That Are
Unknown and Unequal. 476
8.2.7 Confidence Interval for the Mean Difference When the Differences
Have a Normal Distribution . 480
8.3 Confidence Intervals for Population Variances. 482
8.3.1 Confidence Interval for the Population Variance When Sampling
from a Normal Population . 482
X
Contents
8.3.2 Confidence Interval for the Ratio of Population Variances When
Sampling from Independent Normal Distributions. 487
8.4 Confidence Intervals Based on Large Samples . 490
8.4.1 Confidence Interval for the Population Proportion. 491
8.4.1.1 Score Confidence Interval. 496
8.4.1.2 AgrestLCoull Confidence Interval for the Population
Proportion. 498
8.4.1.3 Clopper-Pearson Interval for the Population Proportion 498
8.4.1.4 So Which Confidence Interval Do I Use?. . 498
8.4.2 Confidence Interval for a Difference in Population Proportions . . 506
8.4.3 Confidence Interval for the Mean of a Poisson Random Variable . 508
8.5 Problems . 510
9 Hypothesis Testing 519
9.1 Introduction. 519
9.2 Type I and Type II Errors. 520
9.3 Power Function. 524
9.4 Uniformly Most Powerful Test . 527
9.5 p՜Value or Critical Level. 529
9.6 Tests of Significance . 530
9.7 Hypothesis Tests for Population Means . 532
9.7.1 Test for the Population Mean When Sampling from a Normal
Distribution with Known Population Variance. 532
9.7.2 Test for the Population Mean When Sampling from a Normal
Distribution with Unknown Population Variance. 535
9.7.3 Test for the Difference in Population Means When Sampling from
Independent Normal Distributions with Known Variances. 542
9.7.4 Test for the Difference in Means When Sampling from Independent
Normal Distributions with Variances That Are Unknown but
Assumed Equal . 544
9.7.5 Test for a Difference in Means When Sampling from Independent
Normal Distributions with Variances That Are Unknown and Not
Assumed Equal . 548
9.7.6 Test for the Mean Difference When the Differences Have a Normal
Distribution. 551
9.8 Hypothesis Tests for Population Variances. 555
9.8.1 Test for the Population Variance When Sampling from a Normal
Distribution . 555
9.8.2 Test for Equality of Variances When Sampling from Independent
Normal Distributions. 558
9.9 Hypothesis Tests for Population Proportions . 562
9.9.1 Testing the Proportion of Successes in a Binomial Experiment
(Exact Test). 562
9.9.2 Testing the Proportion of Successes in a Binomial Experiment
(Normal Approximation). 565
9.9.3 Testing Equality of Proportions with Fisher?s Exact Test. 569
9.9.4 Large Sample Approximation for Testing the Difference of Two
Proportions. 574
9.10 Problems . 579
Contents xi
10 Nonparametric Methods 587
10.1 Introduction. 587
10.2 Sign Test . 588
10.2Д Confidence Interval Based on the Sign Test . 588
10.2.2 Normal Approximation to the Sign Test. 589
10.3 Wilcoxon Signed-Rank Test . 594
10.3.1 Confidence Interval for ф Based on the Wilcoxon Signed-Rank Test 599
10.3.2 Normal Approximation to the Wilcoxon Signed-Rank Test . 603
10.4 The Wilcoxon Rank-Sum or the Mann-Whitney U֊Test . . 608
10.4.1 Confidence Interval Based on the Mann-Whitney £/-Test. 612
10.4.2 Normal Approximation to the Wilcoxon Rank-Sum and Mann-
Whitney U-Tests. 615
10.5 The Kruskal-Wallis Test. 622
10.6 Friedman Test for Randomized Block Designs. 629
10.7 Goodness-of-Fit Tests . 634
10.7.1 The Chi-Square Goodness-of-Fit Test. 635
10.7.2 Kolmogorov-Smirnov Goodness-of-Fit Test. 640
10.7.3 Shapiro-Wilk Normality Test. 647
10.8 Categorical Data Analysis. 649
10.8.1 Test of Independence. 651
10.8.2 Test of Homogeneity. 653
10.9 Nonpar ametric Bootstrapping. 656
10.9.1 Bootstrap Paradigm. 656
10.9.2 Confidence Intervals. 665
10.9.3 Bootstrapping and Regression. 677
10.10 Permutation Tests . 681
10.11 Problems . 688
11 Experimental Design 697
11.1 Introduction. 697
11.2 Fixed Effects Model . 702
11.3 Analysis of Variance (ANOVA) for the One-Way Fixed Effects Model . . 703
11.4 Power and the Non-Central F Distribution . 709
11.5 Checking Assumptions. 718
11.5.1 Checking for Independence of Errors. 719
11.5.2 Checking for Normality of Errors. 720
11.5.3 Checking for Constant Variance. 722
11.6 Fixing Problems . 724
11.6.1 Non-Normality. 725
11.6.2 Non-Constant Variance. 726
11.7 Multiple Comparisons of Means. 730
11.7.1 Fisher’s Least Significant Difference. 731
11.7.2 The Tukey’s Honestly Significant Difference. 732
11.7.3 Displaying Pairwise Comparisons . 733
11.8 Other Comparisons among the Means . 733
11.8.1 Orthogonal Contrasts. 734
11.8.2 The Scheffe Method for All Contrasts. 740
11.9 Summary of Comparisons of Means. 740
11.10 Random Effects Model (Variance Components Model) . 745
11.11 Randomized Complete Block Design . 748
11.12 Two-Factor Factorial Design . 760
xii Contents
11.13 Problems . 771
12 Regression 781
12.1 Introduction. 781
12.2 Simple Linear Regression . 783
12.3 Multiple Linear Regression . 784
12.4 Ordinary Least Squares . 785
12.5 Properties of the Fitted Regression Line. 788
12.6 Using Matrix Notation with Ordinary Least Squares . 789
12.7 The Method of Maximum Likelihood. 796
12.8 The Sampling Distribution of /3. 797
12.9 ANOVA Approach to Regression . 800
12.9.1 ANOVA with Simple Linear Regression. 801
12.9.2 ANOVA with Multiple Linear Regression. 805
12.9.3 Coefficient of Determination. 806
12.9.4 Extra Sum of Squares. 807
12.9.4.1 Tests on a Single Parameter . 812
12.9.4.2 Tests on Subsets of the Regression Parameters. 815
12.10 General Linear Hypothesis. 816
12.11 Model Building. 822
12.11.1 Testing-Based Procedures. 822
12.11.1.1 Backward Elimination. 822
12.11.1.2 Forward Selection. 822
12.11.1.3 Stepwise Regression. 822
12.11.1.4 Criterion-Based Procedures. 829
12.11.1.5 Summary. 834
12.11.2 Diagnostics. 834
12.11.2.1 Checking Error Assumptions. 834
12.11.2.1.1 Assessing Normality and Constant Variance 836
12.11.2.1.2 Testing Autocorrelation . 836
12.11.2.2 Identifying Unusual Observations. 838
12.11.2.3 High Leverage Observations. 844
12.11.3 Transformations. 850
12.11.3.1 Collinearity. 853
12.11.3.2 Transformations for Non-Normality and Unequal Error
Variances. 856
12.12 Model Validation. 862
12.12.1 The Validation Set Approach. 863
12.12.2 Leave-One-Out Cross-Validation. 864
12.12.3 fc-Fold Cross-Validation. 865
12.13 Interpreting a Logarithmically Transformed Model . 871
12.14 Qualitative Predictors . 873
12.15 Estimation of the Mean Response for New Values X/ 880
12.16 Prediction and Sampling Distribution of New Observations ^(new) · · · · 880
12.17 Simultaneous Confidence Intervals . 883
12.17.1 Simultaneous Confidence Intervals for Several Mean Responses —
Confidence Band. 884
12.17.2 Predictions of g New Observations. 884
12.17.3 Distinguishing Pointwise Confidence Envelopes from Confidence
Bands. 884
12.18 Problems . 891
Contents xiii
A R Commands 903
B Quadratic Forms and Random Vectors and Matrices 917
B.l Quadratic Forms . 917
B.2 Random Vectors and Matrices . 918
B.3 Variance of Random Vectors . 918
Bibliography 921
Index 931 |
any_adam_object | 1 |
author | Ugarte, María Dolores Militino, Ana F. Arnholt, Alan T. |
author_GND | (DE-588)1115277138 (DE-588)1115277596 (DE-588)1115277707 |
author_facet | Ugarte, María Dolores Militino, Ana F. Arnholt, Alan T. |
author_role | aut aut aut |
author_sort | Ugarte, María Dolores |
author_variant | m d u md mdu a f m af afm a t a at ata |
building | Verbundindex |
bvnumber | BV042926314 |
callnumber-first | Q - Science |
callnumber-label | QA273 |
callnumber-raw | QA273.19.E4 |
callnumber-search | QA273.19.E4 |
callnumber-sort | QA 3273.19 E4 |
callnumber-subject | QA - Mathematics |
classification_rvk | QH 231 SK 800 SK 850 ST 601 |
classification_tum | DAT 368f MAT 620f |
ctrlnum | (OCoLC)923375510 (DE-599)BVBBV042926314 |
dewey-full | 519.20285 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.20285 |
dewey-search | 519.20285 |
dewey-sort | 3519.20285 |
dewey-tens | 510 - Mathematics |
discipline | Informatik Mathematik Wirtschaftswissenschaften |
edition | Second editon |
format | Book |
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genre | 1\p (DE-588)4006432-3 Bibliografie gnd-content |
genre_facet | Bibliografie |
id | DE-604.BV042926314 |
illustrated | Illustrated |
indexdate | 2024-07-20T05:42:53Z |
institution | BVB |
isbn | 9781466504394 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028353500 |
oclc_num | 923375510 |
open_access_boolean | |
owner | DE-739 DE-29T DE-473 DE-BY-UBG |
owner_facet | DE-739 DE-29T DE-473 DE-BY-UBG |
physical | XXXIII, 949 Seiten Illustrationen |
publishDate | 2016 |
publishDateSearch | 2016 |
publishDateSort | 2016 |
publisher | CRC Press |
record_format | marc |
series2 | A Chapman & Hall book |
spelling | Ugarte, María Dolores Verfasser (DE-588)1115277138 aut Probability and statistics with R María Dolores Ugarte ; Ana F. Militino ; Alan T. Arnholt Second editon Boca Raton, Fla. CRC Press [2016] 2016 XXXIII, 949 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier A Chapman & Hall book Datenverarbeitung R (Computer program language) Probabilities Data processing Mathematical statistics Data processing S (Computer system) R Programm (DE-588)4705956-4 gnd rswk-swf Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Statistik (DE-588)4056995-0 s Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s R Programm (DE-588)4705956-4 s b DE-604 Militino, Ana F. Verfasser (DE-588)1115277596 aut Arnholt, Alan T. Verfasser (DE-588)1115277707 aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028353500&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Ugarte, María Dolores Militino, Ana F. Arnholt, Alan T. Probability and statistics with R Datenverarbeitung R (Computer program language) Probabilities Data processing Mathematical statistics Data processing S (Computer system) R Programm (DE-588)4705956-4 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Statistik (DE-588)4056995-0 gnd |
subject_GND | (DE-588)4705956-4 (DE-588)4064324-4 (DE-588)4056995-0 |
title | Probability and statistics with R |
title_auth | Probability and statistics with R |
title_exact_search | Probability and statistics with R |
title_full | Probability and statistics with R María Dolores Ugarte ; Ana F. Militino ; Alan T. Arnholt |
title_fullStr | Probability and statistics with R María Dolores Ugarte ; Ana F. Militino ; Alan T. Arnholt |
title_full_unstemmed | Probability and statistics with R María Dolores Ugarte ; Ana F. Militino ; Alan T. Arnholt |
title_short | Probability and statistics with R |
title_sort | probability and statistics with r |
topic | Datenverarbeitung R (Computer program language) Probabilities Data processing Mathematical statistics Data processing S (Computer system) R Programm (DE-588)4705956-4 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Statistik (DE-588)4056995-0 gnd |
topic_facet | Datenverarbeitung R (Computer program language) Probabilities Data processing Mathematical statistics Data processing S (Computer system) R Programm Wahrscheinlichkeitsrechnung Statistik |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028353500&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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