Composition of Data

1. observations of one or more attributes on each of a number (n) of individual units
2. these attributes usually called random variables
3. e.g., "country represented" by athletes in the Olympics; "period of loan" in a library's study of book lending

1. qualitative/categorical

1. no sense of ordering involved
2. categories don't overlap
3. e.g., red hair and black hair

1. quantitative

1. a definite sense of ordering
2. e.g., more students in a class of 50 than in one of 40
3. 3 kinds: (a) discrete - counts that can take only integer values 0,1,2,3...; continuous - any value within the range of feasible values of the attribute - e.g., height; (c) ordinal - e.g., third steps, fifth from the end

1. generally limited to counting number of items in different categories

1. for small samples, use tally system
2. for larger samples, use computer

1. either way, end product is a frequency table (see 2-Way Frequency Table of Degree by Sex)
2. 2 methods of presentation commonly used for information presented in a frequency table:

1. bar diagram - can misrepresent truth; therefore, height of diagram should be between three-quarters and one-and-a-half times the width
2. pie diaram - numbers of degrees in the slices proportional to the frequencies; i.e., x = 360 x proportion in category

1. with discrete data having only a moderate number of possible values, can use a tally chart to construct a frequency table for the number of times each possible value occurs (e.g., number of children of 20 part-time teachers age 40)
2. these frequencies could be presented in a variant of the bar diagram called a histogram
3. with continuous data, an infinite number of different values are possible; some degree of arbitrariness necessary in the formation of classes

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Men Women Total

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BSc (Agriculture) 103 48 155

BSc (Engineering) 304 30 334

BSc (Forestry) 93 7 100

BSc (Pure Science) 636 635 1271

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Total 1140 740 1860

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* Margins of table ("Total") give the one-way tables for type of degree and sex.