Create a prediction model for the water usage, including an assessment of which variables contribute in a useful way to the prediction and the strength of their impact;
o Hint: predictions can be made with regression models.
o Hint: remember that you may need to transform the dependent variable (e.g. by taking the log) so that it is more like a Normal distribution.
• Include an assessment of which variables contribute in a useful way to the prediction and the strength of their impact.
• Include an assessment of how well the model is able to carry out its prediction;
o Hint: one thing you could do here is use measures of how well the model fits the data such as R2.
• Include appropriate checks on any assumptions made for the analysis technique(s) used.
o Hint: find out what assumptions are made and how to check them using graphs/tests.
Please note that you will not get credit for doing work that is outside the scope of what is being asked for.
Please use the following headings in your report which must be in WORD.
• Title page/contents page. OPTIONAL. If you wish to include a title page and contents page, please do so but they will not be marked. Do NOT include your name here (or on any header/footer) as the work should be submitted (and thus marked) anonymously.
• Introduction. Please use this text and this text alone because you have already undertaken part 1 of the assignment: “The objectives are to create prediction models for water usage using data discussed in a previous report”. There are no marks available for this and you will get nothing for doing anything extra.
• Methods. In ONE paragraph, say why the methods you are using (e.g. multiple regression, model selection procedures) to build the prediction models will achieve the objectives.
• Results. Show your prediction model for water usage, including an assessment of which variables contribute in a useful way to the prediction and the strength of their impact.
• Model evaluation. An assessment of how well the model is able to carry out predictions.
• Assumptions. Report the results of checking assumptions for your final model. Note that you should be checking assumptions as you go along, making sure that you are carrying out and reporting on analyses which do satisfy the assumptions.
• Conclusions. One paragraph summarising the main findings from the “Results” and “Model evaluation” sections.
• Appendix. Here you should list the R commands used to undertake the analysis. This will not be marked but it may be useful to help the marker understand what you have done.
• Quality of introduction to the consultancy brief (accuracy and clarity): 10%
• Exploration of the data (appropriate methods used correctly and appropriate conclusions drawn) and the clarity of the reporting of this: 25%
• Concluding suggestions saying what you might find when doing the analyses for part 2 of the assignment (clarity and appropriateness): 5%
• Brief justification of statistical methods (accuracy, appropriateness, level and clarity): 10%
• Application of statistical analyses (correct methods used to an appropriate extent – evidence of this will be seen in the results given in the report) and reporting of results (appropriate choice of results presented and appropriate comments): 30%
o For this, a good piece of work will have a good choice of analysis and what to report, and the commentary is likely to be good. For a poor piece of work, both the choice of analysis and commentary are likely to be poor. For a mediocre piece of work, it is likely that either both the choice of analysis and commentary are mediocre or that one is good and one is poor.
• Checking assumptions and reporting (appropriate methods used correctly and clarity): 10%
• Conclusions (appropriateness, accuracy and clarity): 10%
this assignment depending to part 1 its submitted and i will upload the file later