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Study online with University of New England through Open Universities Australia. Explore all degrees, subjects and short courses now.

Data and Analysis

Introduction to Psychological Design and Statistics

Data Analysis for Business

Statistics

Research Design

HR Analytics

Quantitative Methods for Social Research

UO R for Data Analytics

Statistical Concepts for Science

Basic Statistical Computing Using R

Are you interested in developing and applying statistical models for the natural or social sciences? Do you want to learn more about the principles of designing a data collection? This subject will help you develop the core skills and knowledge needed for experimental designs and applied statistical models that are used in many scientific fields. Studying this subject, you will learn to develop and analyse various types of linear regression models which are the foundation of many statistical analyses. You will also explore some common experimental designs such as factorial design and randomised block design. Focusing on both the theoretical and technical aspects of key statistical concepts, topics include multiple linear regression with quantitative and qualitative explanatory variables, polynomial regression and generalised linear models.

Statistical Modelling and Experimental Design

Innovation in diverse scientific contexts, from livestock experiments to analysis of Martian soils, relies on statistics. Statistical methods are used universally to better understand the importance of observations and experiments, and to help us to investigate and explain the ways complex systems work. This subject offers you an opportunity to develop an introductory understanding of the fundamentals of statistics – invaluable whether you are interested in the life, environmental or physical sciences. Developing your statistical literacy through a combination of theory and hands-on exercises using statistical computing, you will learn how to present and interpret data for a common set of statistical methods.Topics include exploratory data analysis, randomness associated with experimental data, statistical modelling, sampling, probability, regression, analysis of variance, and tests of significance.

Introduction to Statistical Modelling

University of New England Statistics Subjects | Open Universities Australia

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