Module Descriptor School of Computer Science and Statistics
|Module Name||Design and Analysis of Experiments|
|Module Short Title||N/a|
|Contact Hours||Lecture hours:20|
|Module Personnel||Lecturing staff:Dr. Michael Stuart|
On successful completion of this module, students should be able to
This module is concerned with the design of data collection exercises for the assessment of the effects of making deliberate changes to factors associated with a process or system and the analysis of the data subsequently produced.
It should be noted that the nature and degree of control implicit in this description are frequently not attainable in the social sciences, where observational as opposed to experimental studies are the rule and alternative strategies are required to attempt to assure that observed changes caused observed effects. Such observational studies are not pursued in this module.
The simplest experiments involve comparison of process results when a single factor is varied over two possible conditions. When more than two factors are involved, issues regarding the most efficient choice of combinations of factor conditions and ability to detect interactions between factors become important. With many factors and many possible experimental conditions for each factor, the scale of a comprehensive experimental design becomes impractical and suitable strategies for choosing informative subsets of the full design are needed.
The analysis of data resulting from well designed experiments is often very simple and graphical analysis can be very effective. Standard statistical significance tests may be used to assure that apparent effects are real and not due simply to chance process variation. In cases with more complicated experimental structure, a more advanced technique of statistical inference, Analysis of Variance, may be used. Confidence intervals are used in estimating the magnitude of effects.
Case studies and illustrations from a range of substantive areas will be discussed.
The need for experiments
Basic design principles for experiments
Analysis of experimental data
|Recommended Reading List|
|Module Prerequisites||Base module ST7001|
|Academic Year of Data||N/a|