This is an application-oriented course and the approach is practical.
You'll take a look at several statistical techniques and discuss
situations in which you would use each technique, the assumptions made
by each method, how to set up the analysis using IBM SPSS Statistics as
well as how to interpret the results. This includes a broad range of
techniques for exploring and summarizing data, as well as investigating
and testing underlying relationships. You will gain an understanding of
when and why to use these various techniques as well as how to apply
them with confidence, and interpret their output, and graphically
display the results using IBM SPSS Statistics. This course uses the IBM
SPSS Statistics Base features.
Who Needs to Attend
This course is for anyone who has worked with IBM SPSS Statistics and
wants to become better versed in the basic statistical capabilities of
IBM SPSS Statistics Base. This course targets those with limited or no
statistical background. The course is also an appropriate refresher for
those whose main statistical experience was gained many years ago.
You should have:
- General computer literacy.
- Completion of the "Introduction to IBM SPSS Statistics" and/or "Data Management and Manipulation with IBM SPSS Statistics" courses or experience with IBM SPSS Statistics (Version 15 or later) including familiarity with opening, defining, and saving data files and manipulating and saving output.
- Introduction to Statistical Analysis
- Principles of Research Design and Process
- Understanding Data Distributions - Theory
- Data Distributions for Categorical Data - Practice
- Data Distributions for Continuous Data - Practice
- Making Inferences about Populations from Samples
- Relationships between Categorical Variables: Crosstabs, Chi-square, and Charts
- Independent Samples: T Test: Mean difference between two independent groups
- Paired Samples T Test: Mean difference between related samples
- One-way ANOVA: Mean differences between Multiple Groups
- Bivariate plots and correlations
- Introduction to Regression
- Introduction to Nonparametric Tests