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Viser: Statistical Analysis with R for Dummies

Statistical Analysis with R For Dummies, 1. udgave
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Statistical Analysis with R For Dummies Vital Source e-bog

Joseph Schmuller
(2017)
John Wiley & Sons
232,00 kr.
Leveres umiddelbart efter køb
Statistical Analysis with R For Dummies, 1. udgave

Statistical Analysis with R For Dummies Vital Source e-bog

Joseph Schmuller
(2017)
John Wiley & Sons
191,00 kr.
Leveres umiddelbart efter køb
Statistical Analysis with R For Dummies, 1. udgave

Statistical Analysis with R For Dummies Vital Source e-bog

Joseph Schmuller
(2017)
John Wiley & Sons
163,00 kr.
Leveres umiddelbart efter køb
Statistical Analysis with R for Dummies

Statistical Analysis with R for Dummies

Joseph Schmuller
(2017)
Sprog: Engelsk
John Wiley & Sons, Limited
237,00 kr.
ikke på lager, Bestil nu og få den leveret
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Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: John Wiley & Sons (Marts 2017)
  • ISBN: 9781119337263
Understanding the world of R programming and analysis has never been easier

Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming.

People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.

  • Gets you up to speed on the #1 analytics/data science software tool
  • Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling
  • Shows you how R offers intel from leading researchers in data science, free of charge
  • Provides information on using R Studio to work with R

Get ready to use R to crunch and analyze your data—the fast and easy way!

Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 10 sider kan printes ad gangen
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Detaljer om varen

  • 1. Udgave
  • Vital Source 365 day rentals (dynamic pages)
  • Udgiver: John Wiley & Sons (Marts 2017)
  • ISBN: 9781119337263R365
Understanding the world of R programming and analysis has never been easier

Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming.

People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.

  • Gets you up to speed on the #1 analytics/data science software tool
  • Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling
  • Shows you how R offers intel from leading researchers in data science, free of charge
  • Provides information on using R Studio to work with R

Get ready to use R to crunch and analyze your data—the fast and easy way!

Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: 5 år fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 10 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • 1. Udgave
  • Vital Source 120 day rentals (dynamic pages)
  • Udgiver: John Wiley & Sons (Marts 2017)
  • ISBN: 9781119337263R120
Understanding the world of R programming and analysis has never been easier

Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses—as well as step-by-step guidance that shows you exactly how to implement them using R programming.

People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.

  • Gets you up to speed on the #1 analytics/data science software tool
  • Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling
  • Shows you how R offers intel from leading researchers in data science, free of charge
  • Provides information on using R Studio to work with R

Get ready to use R to crunch and analyze your data—the fast and easy way!

Licens varighed:
Bookshelf online: 120 dage fra købsdato.
Bookshelf appen: 120 dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 10 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Paperback: 464 sider
  • Udgiver: John Wiley & Sons, Limited (Maj 2017)
  • ISBN: 9781119337065
Understanding the world of R programming and analysis has never been easier

Most guides to R, whether books or online, focus on R functions and procedures. But now, thanks to Statistical Analysis with R For Dummies, you have access to a trusted, easy-to-follow guide that focuses on the foundational statistical concepts that R addresses--as well as step-by-step guidance that shows you exactly how to implement them using R programming.

People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it's a free tool that's taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.

  • Gets you up to speed on the #1 analytics/data science software tool
  • Demonstrates how to easily find, download, and use cutting-edge community-reviewed methods in statistics and predictive modeling
  • Shows you how R offers intel from leading researchers in data science, free of charge
  • Provides information on using R Studio to work with R

Get ready to use R to crunch and analyze your data--the fast and easy way

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 à 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 Some Z''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 Ranking in 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 A teachable moment 126 Back to descriptives 126 Skewness 127 Kurtosis 130 Tuning in the Frequency 131 Nominal variables: table() et al 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 a t 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 11: 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-Testing in 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-Distributions 226 Visualizing F-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 277 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 Th
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