Applied Statistics and Research Methods

University of Newcastle

Course Description

  • Course Name

    Applied Statistics and Research Methods

  • Host University

    University of Newcastle

  • Location

    Newcastle, Australia

  • Area of Study

    Research Methodology, Statistics

  • Language Level

    Taught In English

  • Prerequisites

    Assumed knowledge
    STAT1070 or STAT2010

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Host University Units

  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4 - 6
  • Overview

    This is an applied Statistics course which will meet the needs of practitioners in a wide range of science-related disciplines as well as budding statisticians. STAT2000 builds upon the basic techniques taught in the STAT1070 course. Practical data analysis is experienced including how to design appropriate research studies and collect data.


    Learning outcomes
    On successful completion of the course students will be able to:

    1. Recognise the role of statistical methods in the development of scientific knowledge;

    2. Select and implement appropriate standard experimental and observational study designs for collection of valid data in order to solve problems and answer research questions;

    3. Select appropriate statistical methods to analyse particular types of data;

    4. Understand the concepts of linear statistical models for a single response variable and multiple independent predictor variables

    5. Apply a statistical software package to analyse different data types, interpret results, make conclusions and effectively communicate the outcomes of the analysis.


    The course will cover the following statistical techniques:

    Analysis of Variance (ANOVA)

    • One-way ANOVA
    • Fixed and Random Effects models
    • Hierarchical and factorial ANOVA
    • Associated Randomised, Randomised Complete Block and Latin Square study designs

    Simple Linear Regression

    • Parameter estimation and ANOVA in regression models

    Multiple Regression

    • Parameter estimation and Analysis of Covariance in regression models
    • Model selection

    Logistic Regression

    • Non-parametric (distribution-free) tests

    Data collection and statistical modeling for research

    • Study design and data collection concepts and principles
    • Assumptions underlying statistical methods
    • Power and sample size calculations
    • Goodness of fit tests and model validation


    Contact hours
    Computer Lab
    Face to Face On Campus 2 hour(s) per Week for 11 Weeks

    Face to Face On Campus 2 hour(s) per Week for Full Term

Course Disclaimer

Courses and course hours of instruction are subject to change.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.