Unit 1 Section 1.2.

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Presentation transcript:

Unit 1 Section 1.2

1.2: Data Classification Variables can be classified in two ways: Qualitative Variable– variables that can be placed into distinct categories, according to some characteristic or attribute. Quantitative Variable– variables that are numerical and can be ordered or ranked.

Quantitative Variables Section 1.2 Quantitative Variables There are two types of quantitative variables: Discrete Variables – can be assigned values such as 0, 1, 2, 3. Variables are able to be counted. Continuous Variables – can assume an infinite number of values between any two specific values. Values are obtained by measuring (often include decimals and fractions).

The classification of variables can be summarized as follows: Section 1.2 The classification of variables can be summarized as follows: Data Qualitative Quantitative Discrete Continuous

Section 1.2 Measurement Scales Nominal – classifies data using names, labels, or qualities. Mutually exclusive (non-overlapping) Exhausting categories (not infinite) No order or ranking can be imposed on the data. Lowest level of measurement. Qualitative data only. Examples: eye color, political party, zip code

Section 1.2 Measurement Scales Ordinal – classifies data into categories that can be ranked. Precise differences between the ranks are not meaningful. Second lowest level of measurement Can be qualitative or quantitative. Examples: letter grades, Olympic medals

Section 1.2 Measurement Scales Interval – classifies data into categories that can be ranked and have precise differences. There is no meaningful zero (the number zero represents a position on the scale). Second highest level of measurement Examples: temperature, money in a savings account

Section 1.2 Measurement Scales Ratio - possesses all the characteristics of interval measurement and there exists a true zero. Highest level of measurement Examples: height, weight, time

Homework Page 13: Nominal, Ordinal Ordinal, Interval, Ratio False: Data at the ordinal level can be qualitative or quantitative. False: For data at the ordinal level, you cannot calculate meaningful differences between data entries. False: Less types of calculations can be performed with data at the nominal level than with data at the interval level. False: Data at the ratio level can be put in order.

Homework Pg 13: 7 – 31 ODD