Locate a dataset that can be examined in SAS JMP software. This dataset can be of your own making or downloaded from another source. Note that the dataset does not need to be particularly large or complex, but it should include several columns and at least a few dozen rows. Be sure that the data are primarily numerical in nature, since you will create some summary statistics later in this assignment.
1. Import your dataset into a SAS JMP table. 2. Create a view of your dataset using Stacked Columns. Note that you will need to select a column by which you will group data. The dataset you selected may not have an obvious choice for this. You could add such a column if needed, or perhaps convert an existing column into a format suitable for use in stacking the data in the table. 3. Open a new Word document. Save it as IT527-Unitl-XX.docx, where XX are your initials. Create a title page on your document. On the second page, place a screen shot of your stacked table. Beneath your screen shot, write a brief description (please use correct grammar and complete sentences) describing the process of stacking your table and explaining why such a view of your data might be useful or interesting to a data analyst. 4. Return to your original data table. Create Summary Statistics for your columns. Remember that for non-numerical data, you can count values, but you cannot do other types of statistical evaluations, such as averages. On numerical columns, use a few different statistical measures. For example, on one column, you might choose to use an average, and on another, a median, sum or standard deviation. Do at least three different kinds of statistics but consider more if possible. 5. Take a screenshot of your Summary Statistics and place it in your Unit 1 Word file. Write a short description of what you have done with your data, and why it might be interesting to a data analyst. If necessary, use more than one screen shot and description. 6. Research some common issues with data formatting, transfer and manipulation. write 2-3 paragraphs describing some of the issues you learned about. Describe why such issues might represent a problem for data analysts.
