Due Dates Project Proposal due date:
Case study writeups Practicals Each of the practicals involves carrying out some statistical analysis on small, real-world datasets. You may use any software to complete the assignments; all the data is in comma-separated format which should be readable by most software packages.
If you do not already have a favorite, we encourage you to try out Rwhich is available on any Athena machine. Outside of those, we'll do our best to help, but can't promise to get you unstuck.
Finally, keep in mind that in most cases, each analysis will be a single line of R code; rarely will it be more than five. Please contact us if you find yourself getting bogged down in trying to run the analyses. Also explain and interpret the results of any exploratory data analysis and statisical inference.
Include relevant plots and output to back up your claims; however, we don't want to just see loads of print-outs! Your job is to provide succinct summaries of your analysis, not just copy-paste the computer output. Additional pointers for those using R: This short reference card contains a quick-lookup list of a lot of common functions.
If you need more extensive data manipulation, this card is also a good reference. These assignments should be handed in at the start of class on the day they're due. Practical 2 Case studies Review two of the articles listed below, or of your own choosing.
Each review should be no more than one page. Lists, bullet points, etc. Reviews should consist of: What was the objective of the study? Summarize the hypothesis, design methodology, analysis approach, and major findings.
This is to check whether you understood the study. Was the experimental design appropriate for the study? Provide your reasoning for both sound and unsound aspects. Was the statistical analysis sound? If you choose your own, you should be able to find at least one sound and unsound aspect of the paper's statistical and design methodology.Completed project due date: April 19, presented at poster sessions in lab sections.
General Description For the data analysis project, you address some questions that interest you with the statistical methodology we learn in Statistics Statistical analysis is fundamental to all experiments that use statistics as a research methodology.
Most experiments in social sciences and many important experiments in natural science and engineering need statistical analysis. Oct 03, · One idea that interested me a few years ago was the relationship between the number of goals (6 points) and behinds (1 point) kicked by a team during an Australian Rules Football match.
Using statistics in research involves a lot more than make use of statistical formulas or getting to know statistical software. Making use of statistics in research basically involves Learning basic statistics.
This is an example of a logical step on a statistical investigation. A group of students as research team came up with a problem statement, did data gathering,.
Dec 27, · What interesting topic should I choose for a statistics project? Update Cancel. ad by Jira Software, Atlassian.
(market research, What kind of topic can .