Design of experiments and analysing experimental data

Date:

17/06/2019

Organised by:

The University of Manchester

Presenter:

Marzena Nieroda

Level:

Entry (no or almost no prior knowledge)

Contact:

CMI Short Courses
cmi-shortcourses@manchester.ac.uk
0161 2751980

Map:

View in Google Maps  (M13 9PL)

Venue:

University of Manchester

Description:

This course is designed for those interested in the design, conduct, and analysis of experiments in the social sciences. The course will examine how to design experiments, carry them out, and analyse the experimental data. Positioned in the context of online market research, the course will also cover the use of experiments in market research.

We will discuss various designs and their respective differences, advantages, and disadvantages. In particular, basic and factorial designs are discussed in greater detail. Basic experiments involve a manipulation of one independent variable. Factorial designs involve a manipulation of two or more independent variables (factors). In factorial designs, it is of particular interest to understand how combination (interaction) of the two (or more) factors affects the outcome. Differences between within (paired) and between-groups experiments are explained.

The course includes a review of statistics background that is needed for conducting and analysing experiments. We will start with hypothesis testing and discuss most commonly used techniques for analysing experimental data: t-test, Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA). SPSS software will be used to analyse the data.

Cost:

£195 (£140 for those from educational, government and charitable institutions)

Website and registration:

Region:

North West

Keywords:

Experimental Research , Experimental design, Quasi-Experimental Research, Mixed Methods, Mixing qualitative and quantitative approaches, Data Collection, Survey and Questionnaire Design, Quantitative Data Handling and Data Analysis, SPSS

Related publications and presentations:

Experimental Research
Experimental design
Quasi-Experimental Research
Mixed Methods
Mixing qualitative and quantitative approaches
Data Collection
Survey and Questionnaire Design
Quantitative Data Handling and Data Analysis
SPSS

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