Topic outline
Introduction to R ( 10 Lecture hours)
1.1 The History, starting and exiting R, R environment
1.2 The menus and tools in R
1.3 Loading and Installing Packages, Working directory, getting online help
1.4 Simple manipulations in R/using R as calculator, Warnings, errors and comments in R
1.5 Data types, Reading/importing, and storing data
1.6 Vectors, Matrices, Data frames and Lists
1.7 Data Management in R
Please, read the questions and give your answer(s)
Probability and Sampling Distribution of the sample Mean (12 Lecture hours)
1.1 Probability distributions and Probability
1.2 R as a set of statistical tables
1.3 Simulating the Sampling Distribution of the sample Mean
1.3.1. Loops and conditional execution
1.3.2 Writing user defined Functions
Basic Descriptive Statistics using R (8 lecture hours )
2.1 Illustrations using tables and graphs
2.2 Summary statistics
4. Basic Statistical Models in R (10 Lecture hours)
1.1 Regression and correlation Analysis
1.2 One and two sample t tests
1.3 ANOVA models
1.4 Chi-Square Test of Independence
1.5 Time Series models
1.6 Others
Introduction to SAS (12 Lecture hours)
1.1 SAS Language
1.2 Overview of SAS
1.2.1. Accessing and Exiting SAS; Getting Help; Data Step; SAS Constants
1.2.2. Variables, and Expressions; Input and Output
1.2.3. SAS Procedures for Data Analysis
PROC FREQ, PROC MEANS, PROC CORR, PROC REG
1.2.4. SAS Procedures for Graphing PROC PLOT, PROC GPLOT, PROC CHART, PROC GCHART