یادگیری علم داده با استفاده از SAS Studio: راهنمای شروع سریع

Do you want to create data analysis reports without writing a line of code? This book introduces SAS Studio, a free data science web browser-based product for educational and non-commercial purposes. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. It is easier to learn SAS Studio than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. The book includes a case study about analyzing the data required for predicting the results of presidential elections in the state of Maine for 2016 and 2020. In addition to the presidential elections, the book provides real-life examples including analyzing stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS Studio. You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS Studio graphical user interface. The book includes explanations of the code that SAS Studio generates automatically. You will learn how to edit this code to perform more complicated advanced tasks. The book introduces you to multiple SAS products such as SAS Viya, SAS Analytics, and SAS Visual Statistics.**What You Will Learn** * Become familiar with SAS Studio IDE * Understand essential visualizations * Know the fundamental statistical analysis required in most data science and analytics reports * Clean the most common data set problems * Use linear progression for data prediction * Write programs in SAS * Get introduced to SAS-Viya, which is more potent than SAS studio **Who This Book Is For** A general audience of people who are new to data science, students, and data analysts and scientists who are experienced but new to SAS. No programming or in-depth statistics knowledge is needed. Table of Contents 5 About the Author 10 About the Technical Reviewer 11 Introduction 12 Part I: Basics 15 Chapter 1: Data Science in Action 16 Data Science Process 17 Case Study: Presidential Elections in Maine 18 Population 18 Gender 20 Race 22 Age 23 Voter Turnout 24 Winning Candidates in 2012 25 Categories/Issues 27 Issues Facing the Country 27 Categories: Issues Facing Maine 28 Factors Affecting Maine’s Economy 29 Comparing the Unemployment Rate of Maine to That of the Rest of the States 29 Median Income for Maine 29 How Did Exit Polls Show the Income Factor in the 2016 Election in Maine? 30 Reviewing Past Elections to See if There Are Any Predictable Outcomes (Patterns) 31 Modeling 32 My 2016 Predictions 32 My 2020 Predictions 33 Summary 34 Chapter 2: Getting Started 35 How Do You Install SAS Studio? 35 What Is SAS and SAS Studio? 35 Tour 36 Tasks 41 Reports 42 Graphs 44 Snippets 46 So, What Are Snippets? 46 Example to Use Ready-Made Snippet 46 To Create Your Own Snippets 48 Main Components of a SAS Program 49 Data Step 50 Variable Types 50 Proc Step 50 Libraries 50 Accessing Your Existing Local Files 50 The First Method 51 The Second Method 52 Accessing Data in SAS Libraries 52 How Do You Distinguish Between Permanent and Temporary Libraries? 52 Create a New Library 53 Library Naming Conventions 53 Add a New Table to the Library 56 INFILE technique 60 Summary 62 Chapter 3: Data Visualization 63 Scatter Plot 63 Scatter Plot Code 68 Scatter Plot Relationships 69 Plotting More Than One Scatter Plot in the Same Image 70 Histogram 73 Appearance Tab 75 Series Plot 79 Bar Chart 83 How Do You Sort a Bar Chart? 85 Create a Histogram Using a Bar Chart 90 Bubble Chart 95 Maps 101 Bubble Map 101 Cluster Analysis 110 Summary 114 Part II: More Programming 115 Chapter 4: Statistical Analysis and Linear Models 116 Statistical Analysis 116 One-Way Frequency 116 Summary Statistics 119 Correlation Analysis 120 T-Tests 127 One-Sample T-tests 127 Paired-sample T-test 129 Two-Sample T-tests 131 Linear Models 132 One-Way ANOVA 133 N-Way ANOVA 137 Summary 142 Chapter 5: Advanced Data Preprocessing and Feature Engineering 143 Comment Statement 143 Arithmetic Operators 144 How to Represent Missing Values in Raw Data 144 Comparison Operators 145 PROC SQL Statement 146 SELECT-WHERE Statement 148 WHERE Clause 148 SELECT-WHEN-OTHERWISE Statement 150 DO Loops 152 Summary 156 Chapter 6: Preparing Data for Analysis 157 Label 157 Format 160 Create New Variables 162 Rearrange the Dataset Variables 164 IF Statement 165 IF (Condition) Without THEN statement 166 IF-THEN Statement 169 IF-THEN-ELSE Statement 172 DROP Statement 174 SET Statement 175 Summary 177 Part III: Advanced Topics 178 Chapter 7: Regression 179 Simple Linear Regression 179 Multiple Linear Regression 184 Logistic Regression 191 Summary 194 Chapter 8: SAS Visual Statistics: Viya 195 About SAS Studio, SAS Visual Statistics, SAS Visual Analytics, and SAS Viya 195 SAS Viya Tour 196 Map of Counties 198 SAS Visual Statistics: First Report 202 Histogram 206 Word Cloud 209 Bar Chart 212 Butterfly Chart 215 Summary 217 Chapter 9: What Is Next? 218 Reports: How Do You Present Your Results? 219 How Do You Write Your Results, Keeping Your Audience in Mind? 219 How Can You Make Money Online from Data Science? 220 Teaching Online 221 Writing Online 221 Kaggle-Zillow Competition 222 Harvard University, Extension School: Data Science Graduate Professional Certificate 223 SAS Certification 225 Stay in Touch 226 Summary 226 Appendix: Resources 227 Index 229 Do you want to create data analysis reports without writing a line of code? This book introduces SAS Studio, a free data science web browser-based product for educational and non-commercial purposes. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. It is easier to learn SAS Studio than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. The book includes a case study about analyzing the data required for predicting the results of presidential elections in the state of Maine for 2016 and 2020. In addition to the presidential elections, the book provides real-life examples including analyzing stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS Studio. You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS Studio graphical user interface. The book includes explanations of the code that SAS Studio generates automatically. You will learn how to edit this code to perform more complicated advanced tasks. The book introduces you to multiple SAS products such as SAS Viya, SAS Analytics, and SAS Visual Statistics. What You Will Learn Become familiar with SAS Studio IDE Understand essential visualizations Know the fundamental statistical analysis required in most data science and analytics reports Clean the most common data set problems Use linear progression for data prediction Write programs in SAS Get introduced to SAS-Viya, which is more potent than SAS studio Who This Book Is For A general audience of people who are new to data science, students, and data analysts and scientists who are experienced but new to SAS. No programming or in-depth statistics knowledge is needed. Front Matter ....Pages i-xvii Front Matter ....Pages 1-1 Data Science in Action (Engy Fouda)....Pages 3-21 Getting Started (Engy Fouda)....Pages 23-50 Data Visualization (Engy Fouda)....Pages 51-102 Front Matter ....Pages 103-103 Statistical Analysis and Linear Models (Engy Fouda)....Pages 105-131 Advanced Data Preprocessing and Feature Engineering (Engy Fouda)....Pages 133-146 Preparing Data for Analysis (Engy Fouda)....Pages 147-167 Front Matter ....Pages 169-169 Regression (Engy Fouda)....Pages 171-186 SAS Visual Statistics: Viya (Engy Fouda)....Pages 187-209 What Is Next? (Engy Fouda)....Pages 211-219 Back Matter ....Pages 221-226