What types of macroeconomic variables are important to the success of your product? Identify three numerical variables that will be included in your analysis. For each variable you select, define the variable then explain the type of variable then justify why you selected each variable. (12 marks)

• Student Guidance
  • Open the dataset and read through the list of indicators. For example, if you were selling children's books, finding numerical variables relating to children or literacy or education or book sales would be excellent variables to use.
  • Recall from Chapter 1 that variables can be classified in two ways:
    • Categorical (nominal, ordinal)
    • Numerical (interval, ratio - which can be either discrete, continuous)

Q2.2. Select and/one categorical variable from the dataset. Define the variable. Justify why you selected that variable and how you created the categorical variable. (3 marks)

• Student Guidance
  • There are three approaches to select and/or create a categorical variable given the dataset that you must work with:
    • Approach 1: The variable itself is naturally categorical. The variable name implies a category, or the data is in a percentage format (but not a rate of change).
    • Approach 2 categorical variable from a numerical variable
      • For example, if the variable is number of unemployed people
      • You select a specific time frame such as 30 years (1990 to 2020).
      • You can create categories such as "High", "Medium", and "Low"
      • You can define rules such as "a year with unemployment over 200000 is considered High or if the unemployment number represents a percentage of the population higher than 7% it is considered High")
      • Then, you can replace the numerical value with the category type for each data point from 1990 to 2020
    • Approach 3: Integrate the data set by aggregating categories of variables
      • For example, from the data set, select and download all indicators related to Female Population such as "Female population by age, female 0-4" to "Female population by age, 100+"
      • You select a specific time frame such as 30 years (1990 to 2020).
      • The variable is Female Population, the categories are the age intervals (which you could collapse down into a lot less categories, and the population amount for each interval is the frequency (probably better expressed in a percentage format....)

Q2.3. For each variable (all four), what time frame will you use for each variable? Discuss and justify