Nadeem Shafique Butt

Introduction to statistical analysis
Course goals and methods
Basic steps of research process
Populations and samples
Research design
Independent and dependent variables
Levels of measurement and statistical methods
Data checking
Introduction
Viewing a few cases
Minimum, maximum, and number of valid cases
Data validation: data preparation add-on module
Data validation rules
When data errors are discovered
Summary  exercises
Describing categorical data
Why summaries of single variables?
Frequency analysis
Standardizing the chart axis
Pie charts
Summary exercises
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
Appendix: standardized (z) scores
Summary exercises
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: beyond crosstabs
Appendix: association measures
Summary exercises
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
Appendix: paired t test
Appendix: normal probability plots
Summary exercises
Mean differences between groups: one factor ANOVA
Introduction
Extending the logic beyond two groups
Exploring the data
One-factor ANOVA
Post hoc testing of means
Graphing the mean differences
Appendix:  group differences on ranks
Summary exercises
Bivariate plots and correlations: scale variables
Introduction
Reading the data
Exploring the data
Scatterplots
Correlations
Summary  exercises
Introduction to regression
Introduction and basic concepts
The regression equation and fit measure
Residuals and outliers
Assumptions
Simple regression
Summary exercises
Introduction to multiple regression
Multiple regression
Multiple regression results
Residuals and outliers
Summary exercises
Books
Discovering statistics using spss by andy field.
Statistics for environmental science and management by bryan f.j. Manly
Statistics for environmental engineers by paul mac berthouex and linfield c. Brown
Using statistics to understand the environment by c.philip wheater and penny a.cook