Applied Statistical Procedures

This is an intermediate, applied course covering a range of the most commonly used statistical procedures. It aims to provide participants with an ability to understand, run and interpret these procedures.This course will further enhance your ability to understand research based literature where these procedures were employed.

 

The level falls between ‘Fundamentals of Statistics’, and the more detailed single procedure based courses covering topics such as SEM, Multiple Regression, and Factor Analysis.  This course will cover a range of the most commonly used statistical procedures, and it aims to provide participants with an ability to understand, run and interpret these procedures.  The course is taught from an applied prospective, with questions encouraged. The statistical package Employed will be SPSS. No prior knowledge of SPSS is required.

 

You will be exposed to a variety of research scenarios and to the logic of statistical procedure selection and application. This course will provide a good foundation for progression to the more detailed courses in (Multiple) Regression, Factor Analysis, SEM and Latent Variables using Mplus. On completing this course you should be able to read and understand literature where these procedures are reported, select the appropriate statistical procedure for research, run the procedure, and report the results from an informed base of understanding.

 

The target audience for this course range from Qualitative researchers wanting to gain Quantitative skills, to Quantitative researchers wanting to broaden their understanding across procedures, or to become more comfortable with covariance prior to taking SEM.

 

 

COURSE SYLLABUS
Day 1
The context of quantative research in relation to qualitative research. The language of quantitative researc, and the required fundamentasl of SPSS.

Day 2
Reliability, Correlations, Controllong for Confounding Variables, Chi Squares, and T-Tests

Day 3
ANOVAS, ANCOVAS, Factoral ANOVAS, MANOVAS and Non-Parametric Tests.

Day 4
Simple Regression, Multiple Regression, Discriminate Analysis and Factor Analysis

Day 5
Testing Normality, Data Transformations, Validity, Reporting and Ethics; plus individual sessions

 

The procedures that will be covered will include the following:
• The frequency based statistics of Chi Square Goodness of Fit and Chi Square Test of Association.
• The Parametric test of difference statistics of T-tests, ANOVA, ANCOVA, MANOVA, and MANCOVA. Factorial analysis with multiple independent variables will also be covered along with Repeated Measures ANOVA.
• The Non-Parametric test of difference statistics of Mann-Whitney, Wilcoxon, Friedmans Analysis of Variance, and Kruskal Wallis.
• The statistics to predict and to explain variance of Simple Regression, Multiple Regression, Discriminant Analysis and Multiple Discriminant Analysis.
• The data reduction technique of Factor Analysis

Other considerations covered in this course will be:
• Power, the data and statistics that are most powerful, and techniques for increasing statistical power.
• How to determine the best procedure for the demands of the research
• Data transformation to increase power and allow parametric procedures to be employed when data can be appropriately adjusted.
• The important interplay between effect size and significance.
• The integration of statistical results into reports.
 

 

 
Level 2 - runs over 5 days
Instructor: 

Dr Gordon Emmerson is a specialist in quantitative research. He taught undergraduate and postgraduate statistics programs at Victoria University within the Psychology Department, where he currently holds the position of Honory Fellow. He coordinated a major in Social Research Methods. Gordon was employed as a statistical/methods advisor to university staff in the US at Kansas State University in the late 1980s. He is an experienced group facilitator and regularly conducts workshops across a range of topic areas. He is an experienced user of data management and statistical packages including SPSSwin, Excel and Access. He has also undertaken a number of consultancies in quantitative research in the health and education sector.

Course dates: Monday 28 September 2015 - Friday 2 October 2015
Course status: Course completed (no new applicants)
Week: 
Week 1
Recommended Background: 

Participants should have an understanding of elementary statistics equivalent to the syllabus of Fundamentals of Statistics. This lab based course requires students to follow instruction in running and interpreting a range of statistical procedures. It is assumed that participants will have little or no familiarity with at least some of the procedures presented.

The statistical package employed will be SPSS. No prior knowledge of SPSS is required.

 

Course fees
Member: 
$1,870
Non Member: 
$3,485
Full time student Member: 
$1,870
Program: 
Spring Program 2015
Notes: 

The instructor's bound, book length course notes will serve as the course text.

 

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