MAS183 Statistical Data Analysis 1 Project Description For the project you should choose a problem that is relevant to your subject area or that you have an interest in. It is acceptable to choose a problem that you think you already know the answer to - you will not be marked according to whether you have made any wonderful discoveries (or not) but according to your statistical presentation and methodological skills. Examples are included below. However, you should think of your own problem to investigate and you should collect your own data. If you find it necessary to use someone else's problem or data for a project (not recommended), make sure you acknowledge the source in an appropriate way (to avoid plagiarism). When choosing your project try to keep it simple, or at least choose a project that will not require too much time to collect the data (perhaps by choosing something that you normally anyway, such as cooking, driving, etc.). It is better to perform and document a relatively simple project well than to attempt an extremely ambitious project poorly. However, do not be discouraged from using statistics beyond the statistics we cover in MAS183. The project consists of the following steps (note this is what you need to do - see the marking guide below for how you should present your project): 1. Choose a fairly specific problem that you would like to investigate (see examples below). State this as a research question. 2. give a specific hypotheses that you would like to test. If there are any assumptions you feel you will need to make to address your problem (or wish to make to simplify the problem) note these also. 3. Describe the data that you intend to collect. Describe as precisely as you can in preparation for collecting the data and think about sampling and how to ensure the data you collect is consistent. 4. Think about how you intend to use your data to examine your hypotheses (for example, what type of statistical test do you intend to use). 5. Collect the data. Note any problems encountered whilst collecting the data or any changes that need to be made to your original intended method of collection. Keep a copy the data. 6. Describe the data and use it to address your problem. a. Use descriptive statistics and visualisation(s) to present key features of the data. b. Perform a suitable hypothesis test and/or calculate a confidence interval. Make sure your data is consistent with the assumptions of your statistical method. If you encounter inconsistencies, try to get around the problem. If this is not possible you should briefly discuss the inconsistency. 7. Give the outcome of the analysis and draw a conclusion based on your data.

The final project will be marked out of 20. You should include the following sections: Executive summary or abstract o Summarise the project and it's key outcomes Introduction and data collection o Detail the research question o Detail the data collection and any limitations Methods o Detail the statistical technique selected with a justification o If using a hypothesis test detail the null and alternative hypothesis o Assumptions Analysis o Visualise the data o Report the statistical analysis Conclusion o State the results of the analysis in the context of the research question o State any limitations of the project Notes: those marking the project will have the discretion to award bonus marks for exceptional work (for example an informed discussion of several limitations could be awarded a bonus mark) inconsistencies between sections will result in a deduction of marks

Here are some guidelines as to how the marks will be given [0/1/2 per section]: Executive Summary or Abstract: Overview of the project with key results and conclusion 0. No executive summary or abstract 1. Simple summary but missing some details or poorly written 2. Executive Summary or Abstract contains an overview of the project, key results from the analysis and a conclusion. Introduction: An overview of the research question or project aim. 0. Research question or project aim poorly described 1. Simple question adequately described. 2. Sophisticated research question or project aim Data collection process: A description of the data collected (or obtained) and how it was collected (or obtained). 0. Data collection method unclear 1. Data collection appropriate and adequately described (another student could repeat the project). 2. Data collection appropriate and adequately described with limitations of the approach detailed Visualisation: The data should be visualised with an appropriate visualisation and a comment should accompany it that discusses the features of the visualisation. 0. Inappropriate visualisation and/or no comment. 1. Simple, suitable visualisation and associated comment. 2. Suitable, clean visualisation with title, labels (including units) and accompanying comment that demonstrates an understanding of the data as presented in the visualisation. Methods: A suitable statistical technique should be selected. 0. Inappropriate analysis or no statistical technique used. 1. Appropriate statistical technique selected. 2. Appropriate statistical technique selected with justification. Assumptions: A assumptions detailed and check. 0. No assumptions addressed or incorrect assumptions given the technique 1. Assumptions described correctly. 2. Assumptions described correctly and checked. Analysis: A suitable hypothesis test and/or confidence interval should be presented. 0. Inappropriate analysis or presentation of R code with no explanation 1. Hypothesis test or confidence interval stated or carried out correctly. 2. Hypothesis test or confidence interval stated and carried out correctly with good notation. Conclusion: There should be a carefully worded conclusion that puts the ingredients (population, characteristic of interest in the population, sampling mechanism and data collected) together in a coherent and sensible way. 0. Conclusion that makes a statement about a population that is different to the population that was sampled, sample treated as a population 1. Conclusion is suitable and brings together the research question or project aim and information collected and analysed in the project. Understanding of populations and samples demonstrated. 2. Conclusion brings together the research question or project aim and information collected and analysed in the project. Understanding of populations and samples demonstrated. Limitations and/or recommendations for future project described. Appendix: A technical appendix included 0. No appendix 1. Appendix includes data or analysis (e.g output from R or Excel) 2. Appendix includes data and analysis Communication: Good layout, good writing (grammar, spelling, reads well) 0. Poor layout 1. Simple report but missing some details or poorly written or poorly structured 2. Report is easy to follow and readable