7BSP1177: Statistical Techniques For Business - Statistical Methods - Report Writing Assignment Help

Internal Code : 1AAEIF

Statistical Report Writing Assignment Help

Task: 1 Undertake an exploration of your data to look for initial patterns, possible data entry errors and any inconsistencies, drawing appropriate conclusions and acting on these when conducting the analyses below. For each variable in the dataset, you should do the following 1. Look at how the variable is distributed (e.g. pattern in a histogram/chart), looking for any values that seem to be wrong (and dealing with them in an appropriate way), giving useful summary statistics relating to the location on the number line and spread of the data, and discuss anything you feel is relevant.

• For each continuous variable, you will need a minimum of one chart, perhaps obtained using the command “hist”. If you can think of a good reason for having more than one useful chart per variable then you should act accordingly. You will also want a summary table for each continuous variable (or more than one if you think appropriate).
• For each categorical variable, you will need a minimum of one table, perhaps obtained using the command “table”. If you can think of a good reason for having more than one useful table per variable then you should act accordingly. You will also want a summary table for each categorical variable (or more than one if you think appropriate).
• For both types of variable mentioned above you can use these techniques and perhaps others you find useful in order to look for unusual cases/errors.

2. Look at relationships between pairs of variables that you judge to be relevant with a view to part 2 of the assignment (e.g. tabulations) and discuss anything you feel is relevant.

• When looking at relationships between variables (with a view to the predictions you are being asked to do in part 2 of the assignment), you may want to use some relevant scatterplots obtained by using a command like plot(datasetname$variablename1, datasetname$variablename2). You may want to look at (e.g.) the mean of a relevant continuous variable for different levels of a relevant categorical variable by using a command like tapply(datasetname$continuousvariablename, datasetname$categoricalname, mean).
• Based on what you have done for this part of the work, conclude by suggesting what you might find when doing the analyses for part 2 of the assignment. It does not matter if you are ultimately right or wrong but it is good practice to go into an analysis with some idea of what you expect to find.

Task: 2 1. 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;

• Hint: predictions can be made with regression models.
• 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.

2. Include an assessment of which variables contribute in a useful way to the prediction and the strength of their impact. 3. Include an assessment of how well the model is able to carry out its prediction;

• Hint: one thing you could do here is use measures of how well the model fits the data such as R2.

4. Include appropriate checks on any assumptions made for the analysis technique(s) used.

• Hint: find out what assumptions are made and how to check them using graphs/tests.

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