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: Chi-Square Test
  • Requesting The Chi-Square Test
  • Interpreting The Output
  • Additional Two-Way 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 T-Test 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

1991 US General Social Survey

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