, Chapter l
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Quantitative data Qualitative data
• Numerical • Non-numerical (Categorical)
• Can do calculation • Can not do calculation
Fractions or decimals Integers or whole numbers Classified into categories Rank is meaningful
Continuous data Discrete data Nominal data Ordinal data
(Can measure) (Can count) (Weaker)
Ratio scale Interval scale Eg= soft drinks: Eg= rating:
3 3 Interval scale requires that Pepsi, Cole, Fanta, Sprite Excellent, average, poor
Ratio scale requires that
a zero doesn't mean zero.
a zero value exists.
Eg = 0ºC doesn't mean
Eg= O% for math best = no marks.
nothing = is very cold
Has true zero No true zero
Data type Measurement scale Population data: Is the group of all items of interest.
Nominal Sample data: Is the set of items of interest drawn from
Categorical
Ordinal the population.
Census: Is a survey to collect data on the entire population.
Interval Descriptive statistics:
Quantitative
Ratio
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The process of making an estimate,
Inferential statistics:
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prediction, or decision about a
Elements: Who or what we are collecting data from. (Be specific) population based on sample data.
Variables: What information we are collecting. Time series: A data set that tracks a sample over time.
Type of research design in which you collect
Observation: Everything collected (always equal to no. of elements) Cross - sectional:
data from different individuals at single point
Measurement: No. of elements x no. of variables f in time.
Sample survey: A survey to collect data on a sample.
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