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CHAPTER 3 Graphical Presentations. Types of Variables. Qualitative - categories which can be named - Classification : Fr., So., Jr., Sr. - Occupation Quantitative - “meaningful” numerical values - SAT score - Height, Weight, Age.
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Types of Variables • Qualitative - categories which can be named - Classification : Fr., So., Jr., Sr. - Occupation • Quantitative - “meaningful” numerical values - SAT score - Height, Weight, Age
Quantitative Variables may be discrete or continuous • Discrete - possible values for the variable can be listed - number of brothers - number of Heads out of 10 tosses of a coin • Continuous - different values can be arbitrarily close - height - weight
Blood Group Data – “raw data” Patient #Blood Type 1 O 2 A 3 A 4 O 5 B 6 O 7 A 8 AB . . . . . .
Ways to Display Quantitative Data • APTITUDE TEST scores for 20 applicants : • Raw Data: • 68, 72, 91, 47, 52, 75, 63 55, 65, 35, 84, 45, 58, 61 69, 22, 46, 55, 66, 71 • Ordered List: 22, 35, 45, 46, 47, 52, 55 55, 58, 61, 63, 65, 66, 68 69, 71, 72, 75, 84, 91
HISTOGRAM for quantitative data “sort of like” bar chart represents % by area
Density Scale-sets height of block so that resulting area is % in that class interval % in class intervaldensity scale ( % per unit) = length of class interval
HISTOGRAM --for quantitative data -- represents % by area (use density scale)-- total area in blocks is 100% -- each histogram should have: - title - axes should be “numbered” and labeled BAR CHART --for qualitative data -- represents % by height Summary
(what’s wrong with this histogram?) 40 55 80 95 20 70