A researcher has collected data for 7681 patients who had a procedure performed at Clinic ABC in 2009 that serves the Greater Toronto Area regions (Excel file: Fall Assignment Data.xls). The data includes the unique patient identifier, sex (male = 1; female = 2), age (years) and patient region (Durham = 1; Halton = 2; Peel = 3; York = 4). The researchers also collected some lifestyle data including smoking frequency (every day = 1; some days = 2; not at all = 3) and whether the patient eats herbal supplements (yes = 1; no = 2). The researcher also collected data on the number of times in a week the patient performs vigorous activity (where 99 is the user-defined missing value with the label 'unable to do vigorous activity), the number of times in a week they perform moderate activity (where 99 is the user-defined missing value with the label 'unable to do moderate activity), and the number of times in a week they perform strength activity (where 99 is the user-defined missing value with the label 'unable to do strength activity). Note that for these three activity variables, there are also system-missing values in the dataset. Finally, we have the procedure order date/time, procedure completion date/time and the procedure score.

Before proceeding with any analysis, be sure to:

• Ensure that variables are of correct measure (nominal, ordinal, scale). Remember to also do this for any newly created variables
• Add labels to all categorical variables (remember to also do this for any newly created categorical variables)
• Add missing value labels for the three activity variables (this will be covered in Lab 11)
• For the procedure order and completion date/time variables, in the variable view, under column 'type', ensure that the Date format is set to dd-mmm-yyyy hh:mm.

1. Generate Variable Information and Variable Values tables for the dataset. Copy and paste these generated SPSS tables. Note, while you already know how to generate these tables, you may want to hold off on this question until you learn more about missing values so that you don't have to generate these tables twice.