Statistical analysis with R for dummies:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, New Jersey
John Wiley & Sons, Inc.
[2017]
|
| Schriftenreihe: | ... for dummies
Learning made easy |
| Schlagworte: | |
| Online-Zugang: | Ausführliche Beschreibung Inhaltsverzeichnis |
| Beschreibung: | Umschlag: Leverage R as a powerful statistical tool : test your hypotheses and draw conclusions : use R to give meaning to your data |
| Beschreibung: | xiii, 438 Seiten Illustrationen, Diagramme 24 cm |
| ISBN: | 9781119337065 |
Internformat
MARC
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| 100 | 1 | |a Schmuller, Joseph |d 1947- |e Verfasser |0 (DE-588)1041604041 |4 aut | |
| 245 | 1 | 0 | |a Statistical analysis with R for dummies |c by Joseph Schmuller, PhD |
| 246 | 1 | 3 | |a Statistical analysis with R |
| 264 | 1 | |a Hoboken, New Jersey |b John Wiley & Sons, Inc. |c [2017] | |
| 300 | |a xiii, 438 Seiten |b Illustrationen, Diagramme |c 24 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a ... for dummies | |
| 490 | 0 | |a Learning made easy | |
| 500 | |a Umschlag: Leverage R as a powerful statistical tool : test your hypotheses and draw conclusions : use R to give meaning to your data | ||
| 650 | 0 | 7 | |a Statistik |0 (DE-588)4056995-0 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
| _version_ | 1804177586889162752 |
|---|---|
| adam_text | Contents at a Glance
Introduction.........................................................1
Part 1: Getting Started with Statistical Analysis with R.............i
chapter і: Data, Statistics, and Decisions............................9
chapter 2: R: What It Does and How It Does It........................17
Part 2: Describing Data..............................................49
chapter 3: Getting Graphic...........................................51
chapter 4: Finding Your Center.......................................91
chapter 5: Deviating from the Average...............................103
chapter 6: Meeting Standards and Standings..........................111
chapter 7: Summarizing It All.......................................123
chapter 8: What s Normal?...........................................143
Part 3: Drawing Conclusions from Data...............................161
chapter* The Confidence Game: Estimation............................163
chapter io: One-Sample Hypothesis Testing...........................179
chapter 11: Two-Sample Hypothesis Testing...........................205
chapter i2: Testing More than Two Samples...........................231
chapter із: More Complicated Testing.............................. 255
chapter 14: Regression: Linear, Multiple, and the General Linear Model.277
chapter і* Correlation: The Rise and Fall of Relationships..........313
chapter 16: Curvilinear Regression: When Relationships Get Complicated.335
Part 4: Working with Probability....................................359
chapter 17; Introducing Probability.................................361
chapter 18: Introducing Modeling....................................383
Part 5: The Part of Tens............................................405
chapter і* Ten Tips for Excel Emigres...............................407
chapter 20: Ten Valuable Online R Resources.........................421
Index..................................................................425
Table of Contents _BllBl
INTRODUCTION.........................................................1
About This Book..............................................1
Similarity with This Other For Dummies Book..................2
What You Can Safely Skip.....................................2
Foolish Assumptions..........................................2
How This Book Is Organized...................................3
Part 1 : Getting Started with Statistical Analysis with R.3
Part 2: Describing Data...................................3
Part 3: Drawing Conclusions from Data.....................3
Part 4: Working with Probability..........................3
Part 5: The Part of Tens..................................4
Online Appendix A: More on Probability....................4
Online Appendix B: Non-Parametric Statistics..............4
Online Appendix C: Ten Topics That Just Didn t Fit
in Any Other Chapter......................................4
Icons Used in This Book......................................4
Where to Go from Here........................................5
PART 1: GETTING STARTED WITH STATISTICAL
ANALYSIS WITH R......................................................7
CHAPTER 1: Data, Statistics, and Decisions...........................9
The Statistical (and Related) Notions You Just Have to Know.10
Samples and populations..................................10
Variables: Dependent and independent.....................11
Types of data............................................12
A little probability.....................................13
Inferential Statistics: Testing Hypotheses..................14
Null and alternative hypotheses..........................14
Two types of error.......................................15
CHAPTER 2: R: What It Does and How It Does It.......................17
Downloading R and RStudio...................................18
A Session with R............................................21
The working directory....................................21
So let’s get started, already............................22
Missing data.............................................26
R Functions.................................................26
User-Defined Functions......................................28
Comments....................................................29
R Structures.....................................................29
Vectors.......................................................30
Numerical vectors.............................................30
Matrices......................................................31
Factors.......................................................33
Lists.........................................................34
Lists and statistics..........................................35
Data frames...................................................36
Packages................................,։......................39
More Packages....................................................42
R Formulas.......................................................43
Reading and Writing..............................................44
Spreadsheets..................................................44
CSV files.....................................................46
Text files....................................................47
PART 2: DESCRIBING DATA...................................................49
CHAPTER 3: Getting Graphic.................................................51
Finding Patterns............................................... 51
Graphing a distribution.......................................52
Bar-hopping...................................................53
Slicing the pie...............................................54
The plot of scatter...........................................55
Of boxes and whiskers.........................................56
Base R Graphics..................................................57
Histograms....................................................57
Adding graph features.........................................59
Bar plots.....................................................60
Pie graphs................................................... 62
Dot charts....................................................62
Bar plots revisited...........................................64
Scatter plots.................................................67
Box plots.....................................................71
Graduating to ggplot2............................................71
Histograms....................................................72
Bar plots.....................................................74
Dot charts....................................................75
Bar plots re-revisited........................................78
Scatter plots.................................................82
Box plots.....................................................86
Wrapping Up......................................................89
CHAPTER 4; Finding Your Center.........................................91
Means: The Lure of Averages...................................91
The Average in R: mean()......................................93
What s your condition?.....................................93
Eliminate $-signs forth with().............................94
Exploring the data.........................................95
Outliers: The flaw of averages.............................96
Other means to an end......................................97
Medians: Caught in the Middle.................................99
The Median in R: median()....................................100
Statistics ä la Mode.........................................101
The Mode in R................................................101
CHAPTER 5: Deviating from the Average.................................103
Measuring Variation..........................................104
Averaging squared deviations: Variance and
how to calculate it.......................................104
Sample variance...........................................107
Variance in R.............................................107
Back to the Roots: Standard Deviation........................108
Population standard deviation.............................108
Sample standard deviation.................................109
Standard Deviation in R......................................109
Conditions, Conditions, Conditions...........................110
CHAPTER 6: Meeting Standards and Standings............................111
Catching SomeZ s............................................ 112
Characteristics of z-scores...............................112
Bonds versus the Bambino..................................113
Exam scores...............................................114
Standard Scores in R.........................................114
Where Do You Stand?..........................................117
Rankingin R...............................................117
Tied scores...............................................117
Nth smallest, Nth largest.................................118
Percentiles...............................................118
Percent ranks.............................................120
Summarizing..................................................121
CHAPTER 7: Summarizing It All.........................................123
How Many?....................................................123
The High and the Low.........................................125
Living in the Moments.........................................125
Ateachable moment..........................................126
Back to descriptives.......................................126
Skewness...................................................127
Kurtosis...................................................130
Tuning in the Frequency.......................................131
Nominal variables: table() et al....1.....................131
Numerical variables: hist()................................132
Numerical variables: stem()................................138
Summarizing a Data Frame......................................139
CHAPTER 8: What s Normal?..............................................143
Hitting the Curve.............................................143
Digging deeper.............................................144
Parameters of a normal distribution........................145
Working with Normal Distributions.............................147
Distributions in R.........................................147
Normal density function....................................147
Cumulative density function................................152
Quantiles of normal distributions..........................155
Random sampling............................................156
A Distinguished Member of the Family..........................158
PART 3: DRAWING CONCLUSIONS FROM DATA.................................161
CHAPTER 9: The Confidence Game: Estimation.............................163
Understanding Sampling Distributions..........................164
An EXTREMELY Important Idea: The Central Limit Theorem........165
(Approximately) Simulating the central limit theorem.......167
Predictions of the central limit theorem...................171
Confidence: It Has Its Limits!................................173
Finding confidence limits for a mean.......................173
Fit to at.....................................................175
CHAPTER 10: One-Sample Hypothesis Testing..............................179
Hypotheses, Tests, and Errors.................................179
Hypothesis Tests and Sampling Distributions...................181
Catching Some Z s Again.......................................183
Z Testing in R................................................185
t for One.....................................................187
t Testing in R................................................188
Working with t-Distributions..................................189
Visualizing t-Distributions......................................190
Plotting t in base R graphics.................................191
Plotting t in ggplot2.........................................192
One more thing about ggplot2..................................197
Testing a Variance...............................................198
Testing in R..................................................199
Working with Chi-Square Distributions............................201
Visualizing Chi-Square Distributions.............................201
Plotting chi-square in base R graphics........................202
Plotting chi-square in ggplot2................................203
chapter ii: Two-Sample Hypothesis Testing.................................205
Hypotheses Built for Two.........................................205
Sampling Distributions Revisited.................................206
Applying the central limit theorem............................207
Z s once more.................................................208
Z-testing for two samples In R................................210
t for Two........................................................212
Like Peas in a Pod: Equal Variances..............................212
t-Testingin R....................................................214
Working with two vectors......................................214
Working with a data frame and a formula.......................215
Visualizing the results.......................................216
Like p s and q s: Unequal variances...........................219
A Matched Set: Hypothesis Testing for Paired Samples.............220
Paired Sample t-testing In R.....................................222
Testing Two Variances............................................222
F-testing in R................................................224
F in conjunction with t.......................................225
Working with F-Dlstributions.....................................226
Visualizing T-Distributions......................................226
CHAPTER 12: Testing More than Two Samples.................................231
Testing More Than Two............................................231
A thorny problem..............................................232
A solution....................................................233
Meaningful relationships......................................237
ANOVA in R.......................................................237
Visualizing the results.......................................239
After the ANOVA...............................................239
Contrasts in R................................................242
Unplanned comparisons.........................................243
Another Kind of Hypothesis, Another Kind of Test...............244
Working with repeated measures ANOVA........................245
Repeated measures ANOVA in R................................247
Visualizing the results.....................................249
Getting Trendy.................................................250
Trend Analysis in R............................................254
CHAPTER 13: More Complicated Testing....................................255
Cracking the Combinations......................................255
Interactions................................................257
The analysis................................................257
Two-Way ANOVA in R.............................................259
Visualizing the two-way results.............................261
Two Kinds of Variables... at Once..............................263
Mixed ANOVA in R............................................266
Visualizing the Mixed ANOVA results.........................268
After the Analysis.............................................269
Multivariate Analysis of Variance..............................270
MANOVA in R.................................................271
Visualizing the MANOVA results..............................273
After the analysis..........................................275
CHAPTER 14: Regression: Linear, Multiple, and
the General Linear Model.......................................211
The Plot of Scatter............................................277
Graphing Lines.................................................279
Regression: What a Line!.......................................281
Using regression for forecasting............................283
Variation around the regression line........................283
Testing hypotheses about regression.........................285
Linear Regression in R.........................................290
Features of the linear model................................292
Making predictions..........................................292
Visualizing the scatter plot and regression line............293
Plotting the residuals......................................294
Juggling Many Relationships at Once: Multiple Regression.......295
Multiple regression in R....................................297
Making predictions..........................................298
Visualizing the 3D scatter plot and regression plane........298
ANOVA: Another Look............................................301
Analysis of Covariance: The Final Component of the GLM.........305
But wait — there s more.....................................311
CHAPTER 15: Correlation: The Rise and Fall of Relationships... .313
Scatter plots Again...........................................313
Understanding Correlation.....................................314
Correlation and Regression....................................316
Testing Hypotheses About Correlation..........................319
Is a correlation coefficient greater than zero?............319
Do two correlation coefficients differ?....................320
Correlation in R..............................................322
Calculating a correlation coefficient......................322
Testing a correlation coefficient..........................322
Testing the difference between two correlation coefficients_323
Calculating a correlation matrix...........................324
Visualizing correlation matrices...........................324
Multiple Correlation..........................................326
Multiple correlation in R..................................327
Adjusting R-squared........................................328
Partial Correlation...........................................329
Partial Correlation in R......................................330
Semipartial Correlation.......................................331
Semipartial Correlation in R..................................332
CHAPTER 16: Curvilinear Regression: When Relationships
Get Complicated...............................................335
What Is a Logarithm?..........................................336
What Is e?....................................................338
Power Regression..............................................341
Exponential Regression........................................346
Logarithmic Regression........................................350
Polynomial Regression: A Higher Power.........................354
Which Model Should You Use?...................................358
PART 4: WORKING WITH PROBABILITY........................................359
CHAPTER 17: Introducing Probability....................................361
What Is Probability?..........................................361
Experiments, trials, events, and sample spaces.............362
Sample spaces and probability..............................362
Compound Events...............................................363
Union and intersection.....................................363
Intersection again.........................................364
Conditional Probability.......................................365
Working with the probabilities.............................366
The foundation of hypothesis testing.......................366
Large Sample Spaces.............................................366
Permutations................................................367
Combinations................................................368
R Functions for Counting Rules..................................369
Random Variables: Discrete and Continuous.......................371
Probability Distributions and Density Functions.................371
The Binomial Distribution.......................................374
The Binomial and Negative Binomial in R........................375
Binomial distribution.......................................375
Negative binomial distribution..............................377
Hypothesis Testing with the Binomial Distribution...............378
More on Hypothesis Testing: R versus Tradition..................380
CHAPTER 18: Introducing Modeling.........................................383
Modeling a Distribution.........................................383
Plunging into the Poisson distribution......................384
Modeling with the Poisson distribution......................385
Testing the model s fit.....................................388
A word about chisq.testO....................................391
Playing ball with a model...................................392
A Simulating Discussion.........................................396
Taking a chance: The Monte Carlo method.....................396
Loading the dice............................................396
Simulating the central limit theorem........................401
PART 5: THE PART OF TENS.................................................405
CHAPTER 19: Ten Tips for Excel Emigres...................................407
Defining a Vector in R Is Like Naming a Range in Excel.........407
Operating on Vectors Is Like Operating on Named Ranges.........408
Sometimes Statistical Functions Work the Same Way...............412
... And Sometimes They Don t....................................412
Contrast: Excel and R Work with Different Data Formats.........413
Distribution Functions Are (Somewhat) Similar...................414
A Data Frame Is (Something) Like a Multicolumn Named Range_____416
The sapplyO Function Is Like Dragging...........................417
Using edit() Is (Almost) Like Editing a Spreadsheet............418
Use the Clipboard to Import a Table from Excel into R..........419
CHAPTER 20: Ten Valuable Online R Resources.............................421
Websites for R Users............................................421
R-bloggers..................................................421
Microsoft R Application Network.............................422
Quick-R.....................................................422
RStudio Online Learning...............................422
Stack Overflow........................................422
Online Books and Documentation...........................423
R manuals »423
R documentation.......................................423
RDocumentation........................................423
YOU CANanalytics......................................423
The R Journal »424
INDEX.............................................................425
|
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| id | DE-604.BV044348192 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:50:26Z |
| institution | BVB |
| institution_GND | (DE-588)4101395-5 |
| isbn | 9781119337065 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029751054 |
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| owner | DE-29T DE-384 DE-706 DE-1102 |
| owner_facet | DE-29T DE-384 DE-706 DE-1102 |
| physical | xiii, 438 Seiten Illustrationen, Diagramme 24 cm |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | John Wiley & Sons, Inc. |
| record_format | marc |
| series2 | ... for dummies Learning made easy |
| spelling | Schmuller, Joseph 1947- Verfasser (DE-588)1041604041 aut Statistical analysis with R for dummies by Joseph Schmuller, PhD Statistical analysis with R Hoboken, New Jersey John Wiley & Sons, Inc. [2017] xiii, 438 Seiten Illustrationen, Diagramme 24 cm txt rdacontent n rdamedia nc rdacarrier ... for dummies Learning made easy Umschlag: Leverage R as a powerful statistical tool : test your hypotheses and draw conclusions : use R to give meaning to your data Statistik (DE-588)4056995-0 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Statistical Software / R Statistics Statistik Statistiksoftware / R Statistik (DE-588)4056995-0 s R Programm (DE-588)4705956-4 s DE-604 John Wiley and Sons (DE-588)4101395-5 pbl Erscheint auch als Online-Ausgabe 978-1-119-33709-6 Erscheint auch als Online-Ausgabe 978-1-119-33726-3 http://www.wiley-vch.de/publish/dt/books/ISBN978-1-119-33706-5/ Ausführliche Beschreibung 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=029751054&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schmuller, Joseph 1947- Statistical analysis with R for dummies Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4705956-4 |
| title | Statistical analysis with R for dummies |
| title_alt | Statistical analysis with R |
| title_auth | Statistical analysis with R for dummies |
| title_exact_search | Statistical analysis with R for dummies |
| title_full | Statistical analysis with R for dummies by Joseph Schmuller, PhD |
| title_fullStr | Statistical analysis with R for dummies by Joseph Schmuller, PhD |
| title_full_unstemmed | Statistical analysis with R for dummies by Joseph Schmuller, PhD |
| title_short | Statistical analysis with R for dummies |
| title_sort | statistical analysis with r for dummies |
| topic | Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd |
| topic_facet | Statistik R Programm |
| url | http://www.wiley-vch.de/publish/dt/books/ISBN978-1-119-33706-5/ http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029751054&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT schmullerjoseph statisticalanalysiswithrfordummies AT johnwileyandsons statisticalanalysiswithrfordummies AT schmullerjoseph statisticalanalysiswithr AT johnwileyandsons statisticalanalysiswithr |