Data Collection Creating a Composite Classmate 
Statistical Topic:
Data used in statistics classes can be classified into quantitative (numerical) and categorical ( non-numerical) variables.  A student must be careful in recognizing the type of variables used in any statistical analysis since many analyses can only be used on certain types of variables.  Numerical or quantitative data consists of discrete and continuous variables.  Continuous data can be thought of numbers on a number line with no breaks, such as a weight of 12.3 kgm (don't have to have decimal places).  Discrete data, on the other hand, would have gaps in the numerical continuum because it generally represents a count, say the number of students in a class (data would not be 2.3 children, as statistic like the mean might but not a data value), or the number of yes responses to a survey question.  Categorical variables (sometimes called qualitative variables)  are non-numerical and falls into two types:  data values that can be ordered -ordinal, or non-ordered - nominal.  An example of ordinal data could be year of schooling such as -- freshman, sophomore, junior or senior in college or tenth, eleventh, twelfth grader, a variable which has a visible order.  An example of nominal data would be the gender of a student or the color of a student's eyes where no order occurs. Sometimes categorical variable are coded with numbers. If unsure as to whether these variables are categorical or numerical, ask yourself if you could place a text description in place of the number. 
Student Issue: 
The student will become familiar with characteristics of other classmates in his/her statistics class.  An assortment of variables will be collected from each student illustrating not only the types of variable but how a data set can be generated.  Simple statistical computation such as the mean can start to give the student a way to explain numerical variables in the data set.  Learning about other members of your class can be tremendously helpful in not only learning statistics but  in many other imagineable ways.  Take the time to learn the name and interests of both your classmates and your instructors. You will be surprised how much easier a class can be if you have other people to help you when you get stuck or just need emotional support.
Data Set: 
Collect data from each student and place on one piece of paper or fill out the following table:  Table 1.  Class Data for Appearance and Interest Variables.
Goal of this Data Analysis Lab: 
Using the results of your data collection, create a description of your new composite classmate using the variables generated from Table 1. 
Statistical Techniques:
  1. Each student will fill in their personal information (fictious identity can be created to protect any student).   For each variable in your data set, determine if the data is quantitative-discrete, quantitative-continuous,  categorical-ordinal or categorical-nominal.
  2. Create a name for your composite student consisting of the most frequently occurring letters from the first name variable for the class data set.
  3. Using each of the categorical variables, determine whether each is ordinal or nominal.  Find which observations are repeated most often.
  4. Using each of the quantitative variables, compute the average.
  5. Using the results of  2, 3 and 4, write a paragraph which contains a description of your new composite classmate. Feel free to improvise on other variables not described in this data set if this will help give your classmate a “personality”.
Social Commentary:
  1. Can you think of other variables that might help you learn more about your classmates?
  2. Could the composite classmate you created really exist? Explain why or why not? 
  3. Is a composite classmate the same as a randomly selected student?