A) Sometimes data needs to be re-categorized for proper analysis. A common piece of data that researchers or business analysts re-categorize from being a quantitative, continuous variable into a qualitative, binary variable is age. We normally think of people’s ages as ranging from 0 to a maximum of, well, let’s say 100. But to most folks in the business community, there really is no difference between someone aged 47 or 48 because often their spending habits are exactly the same. Therefore, it is often useful to apply a qualitative label to people’s ages instead of a number because people within the same age brackets (or bins) have similar spending habits, and those spending habits are often quite different from those in other brackets. You hear about the different age brackets colloquially all the time – some people are toddlers, others are teenagers, others are young adults, and still others are retirees or seniors. Isn’t it fair to say that your generation’s purchases of iPads are likely to be radically different from your grandparents? Or that parents will spend more money, as a group, on minivans than teenagers will? Say you are a business analyst at Colgate. Complete the table below by filling in a binary (0, 1) value in every box indicating whether or not that observation falls into the given age category. The age categories we use are the following: toddler (0-3 years old), child (4-12), teenager (13-19), young adult (20-24), parents (25-65), and seniors (66+). Only AGE is reproduced in the table below. AGE TODDLER CHILD TEENAGER Y. ADULT PARENTS SENIORS 19 27 5 65 32 33 71 80 17 24 31 11 52 45 43 50 68 92 B) What advantage do histograms have over frequency distribution tables?
A) Sometimes data needs to be re-categorized for proper analysis. A common piece of data that researchers or business analysts re-categorize from being a quantitative, continuous variable into a qualitative, binary variable is age. We normally think of people’s ages as
Say you are a business analyst at Colgate. Complete the table below by filling in a binary (0, 1) value in every box indicating whether or not that observation falls into the given age category. The age categories we use are the following: toddler (0-3 years old), child (4-12), teenager (13-19), young adult (20-24), parents (25-65), and seniors (66+). Only AGE is reproduced in the table below.
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AGE |
TODDLER |
CHILD |
TEENAGER |
Y. ADULT |
PARENTS |
SENIORS |
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19 |
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27 |
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5 |
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65 |
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32 |
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33 |
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71 |
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80 |
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17 |
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24 |
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31 |
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11 |
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52 |
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45 |
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43 |
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50 |
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68 |
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92 |
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B) What advantage do histograms have over frequency distribution tables?
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