دانلود کتاب Statistics for Big Data for Dummies

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Title Page......Page 3
Copyright Page......Page 4
Table of Contents......Page 7
Introduction......Page 15
About This Book......Page 16
Foolish Assumptions......Page 17
Beyond the Book......Page 18
Where to Go From Here......Page 19
Part I Introducing Big Data Statistics......Page 21
Characteristics of Big Data......Page 23
Graphical EDA techniques......Page 24
Statistical Analysis of Big Data......Page 25
Probability distributions......Page 26
Regression analysis......Page 27
Forecasting techniques......Page 28
Characteristics of Big Data......Page 33
Volume......Page 34
Velocity......Page 35
Relational model databases......Page 36
Hierarchical model databases......Page 38
Network model databases......Page 39
Alternatives to traditional database systems......Page 40
Chapter 3 Using Big Data: The Hot Applications......Page 41
Big Data and Weather Forecasting......Page 42
Big Data and Healthcare Services......Page 44
Big Data and Insurance......Page 45
Big Data and Finance......Page 47
Big Data and Electric Utilities......Page 48
Big Data and Higher Education......Page 49
Nordstrom......Page 50
Amazon.com......Page 51
Big Data and Search Engines......Page 52
Big Data and Social Media......Page 53
The Core Structure: Probability Spaces......Page 55
Discrete Probability Distributions......Page 57
Counting outcomes......Page 58
When only two things can happen: The binomial distribution......Page 59
The normal distribution......Page 63
Introducing Multivariate Probability Distributions......Page 67
Unconditional probabilities......Page 68
Conditional probabilities......Page 69
Some Preliminaries Regarding Data......Page 71
Summary Statistical Measures......Page 72
Measures of central tendency......Page 73
Measures of dispersion......Page 77
The null hypothesis......Page 80
The level of significance......Page 81
The critical value (s)......Page 82
To reject or not to reject, that is the question......Page 83
Measures of association......Page 84
Higher‐Order Measures......Page 88
Skewness......Page 89
Kurtosis......Page 91
Part II Preparing and Cleaning Data......Page 95
Chapter 6 Dirty Work: Preparing Your Data for Analysis......Page 97
Checking your sources......Page 98
Verifying formats......Page 99
Typecasting your data......Page 100
Dealing with datetime formats......Page 101
Taking geography into account......Page 102
How your software thinks about dates......Page 103
Checking discrete data......Page 104
Checking continuous data......Page 105
Missing values......Page 107
Other Common Data Transformations......Page 109
Standard scores......Page 110
Dummy variables......Page 111
Spreadsheet Formats......Page 113
Comma‐separated variables (.csv)......Page 114
Text......Page 115
Microsoft Excel......Page 116
Web formats......Page 118
Microsoft Access (.accdb)......Page 119
MySQL (.frm)......Page 120
Goodness of fit test......Page 121
The chi‐square distribution......Page 122
Computing the test statistic......Page 123
The critical value......Page 127
The decision......Page 128
Kurtosis......Page 129
Computing the test statistic......Page 130
The critical value......Page 131
Missing Data: What’s the Problem?......Page 133
Missingness......Page 134
Deletion techniques......Page 136
Imputation techniques......Page 138
Expectation‐maximization (EM)......Page 141
Chapter 10 Sending Out a Posse: Searching for Outliers......Page 143
Testing for Outliers......Page 144
Graphical tests of outliers......Page 145
Hypothesis tests for outliers......Page 149
Robust Statistics......Page 152
Dealing with Outliers......Page 153
Part III Exploratory Data Analysis (EDA)......Page 155
Chapter 11 An Overview of Exploratory Data Analysis (EDA)......Page 157
Graphical EDA Techniques......Page 158
Histograms......Page 159
Scatter plots......Page 160
Run sequence plot......Page 162
Lag plot......Page 163
Histogram......Page 164
Normal probability plot......Page 165
Interval estimation......Page 166
Hypothesis testing......Page 167
Stem‐and‐Leaf Plots......Page 169
Scatter Plots......Page 171
Box Plots......Page 175
Histograms......Page 177
Quantile‐Quantile (QQ) Plots......Page 179
Autocorrelation Plots......Page 182
Chapter 13 You’re the Only Variable for Me: Univariate Statistical Techniques......Page 187
Counting Events Over a Time Interval: The Poisson Distribution......Page 188
Continuous Probability Distributions......Page 190
The Student’s t‐distribution......Page 191
The lognormal distribution......Page 195
The chi‐square distribution......Page 198
The F‐distribution......Page 201
Chapter 14 To All the Variables We’ve Encountered: Multivariate Statistical Techniques......Page 205
The null hypothesis for two population means......Page 206
Test statistics and critical values for testing hypotheses about two population means......Page 207
Independent populations......Page 208
The case of dependent populations......Page 210
Using Analysis of Variance (ANOVA) to Test Hypotheses about Population Means......Page 213
The F‐Distribution......Page 218
Finding the critical values using the F‐table......Page 219
F‐Test for the Equality of Two Population Variances......Page 220
Test statistic......Page 221
Decision rule......Page 222
Correlation......Page 223
Pearson’s product‐moment correlation coefficient......Page 224
Spearman’s rank correlation coefficient......Page 226
Chapter 15 Regression Analysis......Page 229
Defining the Population Regression Equation......Page 230
Estimating the Population Regression Equation......Page 231
The coefficient of determination (R2)......Page 236
The t‐test......Page 238
Excel......Page 242
Using the p‐value......Page 243
Violations of the assumptions......Page 244
Multiple Regression Analysis......Page 245
Predicting the value of Y......Page 247
Testing the results of the multiple regression equation......Page 248
Multicollinearity......Page 255
Key Properties of a Time Series......Page 257
Cyclical component......Page 258
Multiplicative decomposition......Page 259
Smoothing Techniques......Page 261
Moving averages......Page 262
Centered moving averages with an even period size......Page 264
Exponential smoothing......Page 266
Seasonal Components......Page 269
Modeling a Time Series with Regression Analysis......Page 271
Identifying the trend......Page 272
Estimating the trend......Page 274
Forecasting with time series regression......Page 276
Estimating a quadratic trend......Page 277
Mean absolute deviation (MAD)......Page 281
Mean square error (MSE)......Page 282
Part IV Big Data Applications......Page 283
ARIMA Modeling......Page 285
Testing for stationarity......Page 286
Adjustments for nonstationarity......Page 289
Steps used in ARIMA modeling......Page 290
Moving average (MA) processes......Page 293
Autoregressive (AR) processes......Page 295
Autoregressive moving average (ARMA) processes......Page 297
Autoregressive integrated moving average (ARIMA) processes......Page 299
Simulation Techniques......Page 300
Historical simulation......Page 301
Monte Carlo simulation......Page 304
Chapter 18 Crunching Numbers: Performing Statistical Analysis on Your Computer......Page 311
Key Excel statistical functions......Page 312
Updated statistical functions......Page 318
Analysis ToolPak......Page 321
Programming with Visual Basic for Applications (VBA)......Page 324
R, Matey!......Page 328
Chapter 19 Seeking Free Sources of Financial Data......Page 333
The ticker symbol......Page 334
Downloading historical stock prices......Page 335
Finding stock option prices......Page 336
Analyzing options strategies......Page 337
Other information on Yahoo! Finance......Page 339
Federal Reserve Economic Data (FRED)......Page 340
Finding financial data on FRED......Page 341
Board of Governors of the Federal Reserve System......Page 342
U.S. Department of the Treasury......Page 343
Other Useful Financial Websites......Page 344
Part V The Part of Tens......Page 345
Check Data Formats......Page 347
Verify Data Accuracy......Page 348
Deal with Missing Values......Page 349
Check Your Assumptions about How the Data Is Distributed......Page 350
Back Up and Document Everything You Do......Page 351
What Are the Key Properties of a Dataset?......Page 353
What’s the Center of the Data?......Page 354
How Much Spread Is There in the Data?......Page 355
Is the Data Skewed?......Page 357
What Distribution Does the Data Follow?......Page 358
Are the Elements in the Dataset Uncorrelated?......Page 359
Does the Center of the Dataset Change Over Time?......Page 360
Are There Outliers in the Data?......Page 361
Does the Data Conform to Our Assumptions?......Page 362
Index......Page 363
EULA......Page 387