STAT100 - Research Question Data Set - Explanatory Variables - Statistics Research Assessment Answer

Assessment Task:

STAT100 - Statistics Research Assessment Answer

1. Provide a description of the research question that you are exploring with the data that you collected. You must include the word difference or relationship (or a synonym for either) as well as an adequate and specific description of your variables. Remember also that your response variable must be numerical and your explanatory variable may be categorical or numerical.

2. An original image related to the collection of data must be included in your assignment. The image might be of the setting, subjects (as long as they’re not people – see below), equipment used for measurement, or yourself doing some work etc. You should label this graphic as Figure 1 and provide an appropriate and informative figure title. The figure label and title should appear below the graphic. Please note that:

• The only person that can appear in your image is you. This restriction relates to the need for people to provide written consent for image use.
• The image that you use must be your own image and not a picture that you’ve sourced from elsewhere.
• The maximum filesize for your assignment submission to Moodle is 10MB.
• The image must be inserted within your submission rather than be submitted as a separate file.

3. A table that neatly presents your raw data. Each of the two variables should be listed in a separate column. Each subject should be a row. You should label this table as Table 1 and provide an appropriate and informative title for this table. The table label and title should appear above the table.

4. Provide 1-2 sentences that confirm that the data were collected as per ethics guidelines.

5. Provide an explanation of what, how and where you collected your data. To do this you’ll need to identify who the subjects/cases are and where/how data collection occurred. You’ll need to provide all necessary details on the location, measurement units used, definitions of categories, equipment etc. You must also clearly explain how your sample is random and your observations are independent.

6. Identify the data type (i.e., nominal, ordinal, continuous or discrete) of the response and explanatory variables that you identified in Question 1. Provide support for your answers.

7. Present appropriate summary statistics of both your response and explanatory variables. These summary statistics should be presented within either one or two tables – dependent on your preference and the type of data that you’ve collected. This table (or tables) should not be cut and pasted from RStudio but rather produced within whichever document software (i.e., Microsoft Word, Google Docs etc.) that you’re using. You should label this table (or tables) as Table 2 (and then Table 3 if appropriate) and provide an appropriate and informative title for the table/s. The table label and title should appear above the table.

8. A professional-looking, coloured, well-labelled graphic (i.e., scatterplot, boxplot, histogram, bar-chart, or mosaic chart) of your data produced using RStudio1. The presentation of results in this graphic should relate directly to the research question underlying the data that you have collected. The following should also be included:

You should label your graph as Figure 2 and provide an appropriate and informative title for this figure. The figure label and title should appear below the graphic.

The RStudio code that you used to produce your figure should also be presented. You do not need to include details on loading, attaching, and summarising data – just the code related to the figure itself. Format this code within your document and insert it within a box in your text. Label this boxed code as Figure 3 and provide an appropriate title for this figure. The figure label and title should appear below the boxed code.

9.  A brief summary of the general pattern shown in your graphic (Question 9). For this question focus only on the general pattern that you are seeing in your graphic. You might like to describe aspects such as relative scatter, amount of variability, differences between levels, outliers, and general trends.

10. Provide an interpretation of the summary statistics and graphic (Questions 8 and 9) in relation to your research question (Question 1). More specifically, give some insight into what your results imply about your research question. This interpretation should be completely separate and distinct from the general summary of the graphic that you presented in Question 10.

11. Provide a brief description of one possible confounding variable with an explanation of why you believe that the given variable may have had an impact on your data.

12.  Identify which population you think your sample (i.e., data collected) may refer to. Be as specific as possible and provide appropriate justification for your answer.

13. Using the statistical concepts covered in lectures identify at least two ways in which you may have been able to improve the experimental design of your data collection activities. Provide an explanation for each of the two suggestions.

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