Statistical Computing:
Excel, SPSS, Stata, Minitab, R, Mathematica
Aims and Objectives
The purpose of this course is to introduce students to the use of modern statistical packages for analyzing various types of data commonly encountered in many areas of science. Students with limited computer experience will be introduced to some widely used statistical packages such as Excel, SPSS and R, a free version of S PLUS. They will learn how to use these packages for analyzing various types of real life data. Mathematica will be introduced for symbolic computing with special reference to algebraic manipulation of statistical distributions.
Describing Categorical Data
 Why Summaries of Single Variables?
 Frequency Analysis
 Standardizing the Chart Axis
 Bar Chart, Pie Charts, and clustered bar chart
Exploratory Data Analysis: Scale Data
 Summarizing Scale Variables
 Measures of Central Tendency And Dispersion
 Normal Distributions
 Histograms And Normal Curves
 Using The Explore Procedure: EDA
 Standard Error of The Mean And Confidence Intervals
 Shape of The Distribution
 Boxplots
Probability and Inferential Statistics
 The Nature of Probability
 Making Inferences About Populations From Samples
 Influence of Sample Size
 Hypothesis Testing
 Types of Statistical Errors
 Statistical Significance and Practical Importance
Comparing Categorical Variables
 Typical Applications
 Crosstabulation Tables
 Testing The Relationship: ChiSquare Test
 Requesting The ChiSquare Test
 Interpreting The Output
 Additional TwoWay Tables
 Graphing The Crosstabs Results
 Adding Control Variables
 Extensions
Mean Differences Between Groups: T Test
 Introduction
 Logic of Testing for Mean Differences
 Exploring The Group Differences
 Testing The Differences: Independent Samples T Test
 Interpreting The TTest Results
 Graphing Mean Differences
Bivariate Plots and Correlations: Scale Variables
 Introduction
 Reading The Data
 Exploring The Data
 Scatterplots
 Correlations
Introduction to Regression and Experimental Design
 Introduction And Basic Concepts
 The Regression Equation And Fit Measure
 Residuals And Outliers
 Assumptions
 Simple Regression
Statistical Distributions
 Simulating Statistical distribution
 Plotting Statistical distribution
Mathematical Manipulation
 Arithmetic
 Algebra
 Lists
 Matrices
 Plotting
 Sums, Products and Limits
 Differential Calculus
 Integral Calculus
 Power Series
 Ordinary Differential Equations
 Displaying and Analyzing Data
Case Studies
Text Books
Good, Phillip L (2005) "Introduction to statistics through resampling methods and Microsoft Office Excel", John Wiley & Sons, Inc., Hoboken, New Jersey
Andy Field (2005) "Discovering Statistics Using SPSS, Second Edition", SAGE Publications
Landau, Sabine. (2004) "A handbook of statistical analyses using SPSS", Chapman & Hall/CRC Press LLC
Cohen, Yosef. (2008) "Statistics and data with R : an applied approach through examples", John Wiley & Sons Ltd
Michael J. Crawley (2007) "The R Book", John Wiley & Sons Ltd
McMahon, David (2006) "Beginners Guide to Mathemaica", Chapman & Hall/CRC Press LLC

About
Nadeem Shafique Butt, Associate Professor of Biostatistics at King Abdulaziz University Also Visiting/Adjunct faculty member at University of the Punjab,
Phone:
Fax:

Statistical Computing
 Advance Applied Linear Models
 Advanced Applied Statistics
 Business Statistics
 Categorial Data Analysis
 Decision Models and Risk Analysis
 Introduction to Statistics
 Mathematical Modeling for Business
 Probability and Statistics
 Quantitative Techniques
 Statistical and OR Computing
 Statistical Computing
 Statistical Inference
 Statistics for Enviornmental Engineers
 Statistics for Managers
 Survival Analysis

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