1 Introduction 2 SAS Language 2.1 Proc Step and Data Step 2.2 SAS Logical Library 2.2.1 Access SAS file 2.2.2 View SAS library and file 3 SAS Programming 3.1 Reading data by DATA STEP 3.2 Output format 3.3 Manipulate datasets 3.3.1 SET statement 3.3.2 SORT proc 3.4 Logical statements 3.4.1 IF-THEN statement 3.4.2 SELECT-WHEN statement 3.4.3 DO-ENDS statement 3.4.4 DO-WHILE DO-UNTIL statement 3.5 OPERATIONS 4 Basic statistical analysis 4.1 Descriptive Statistics Proc 4.1.1 MEANS proc 4.1.2 SUMMARY proc 4.1.3 UNIVARIATE proc 4.1.4 TABULATE PROC 4.1.5 GCHART proc 4.1.6 GPLOT proc 4.2 INFERENTIAL Statistics 4.2.1 T-TEST 4.2.2 Chi-square tests 4.2.3 Correlation 4.2.4 Regression

To develop a subclass from a superclass through inheritance (§8.2). To invoke the superclass’s constructors and methods using the super keyword (§8.3). To override methods in the subclass (§8.4). To explore the useful methods (equals(Object), hashCode(), toString(), finalize(), clone(), and getClass()) in the Object class (§8.5, §8.11 Optional). To comprehend polymorphism, dynamic binding, and generic programming (§8.6). To describe casting and explain why explicit downcasting is necessary (§8.7). To understand the effect of hiding data fields and static methods (§8.8 Optional). To restrict access to data and methods using the protected visibility modifier (§8.9). To declare constants, unmodifiable methods, and nonextendable class using the final modifier (§8.10). To initialize data using initialization blocks and distinguish between instance initialization and static initialization blocks (§8.12 Optioanl)

Introduction Examines a de facto standard for external data representation and presentation as well as a set of library procedures used to perform data conversion Describes the general motivations for using an external data representation and the details of one particular implementation

10.1 Introduction 10.2 Empirical Studies and Statistical Inference 10.3 Important Features of Big Data 10.4 Big Data Analysis and Statistics 10.5 Machine Learning and Statistics 10.6 Conclusion

 Data Center Introduction  Data Center Network Architectures  Fat-Tree  VL2  DCell  BCube  FiConn

1. to know the transmission media of data signals, the structure of full-duplex data transmission system and its peration and the coding of data signals 2. to understand the main idea and

▪ Overview ▪ Data Warehousing ▪ Online Analytical Processing ▪ Data Mining

1.1 Understand the need for computerized support of managerial decision making 1.2 Recognize the evolution of such computerized support to the current state—analytics/data science 1.3 Describe the business intelligence (BI) methodology and concepts 1.4 Understand the various types of analytics, and see selected applications 1.5 Understand the analytics ecosystem to identify various key players and career opportunities

Decision Support Systems Data Warehousing Data Mining Classification Association Rules Clustering

Time series vs Cross sectional e Time series data has a temporal ordering unlike cross-section data Will need to alter some of our assumptions to take into account that we no longer have a random sample of individuals Instead. we have one realization of a stochastic(i.e. random) process Economics 20- Prof anderson