BSNS102 1
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Quantitative data is:
Numerical eg. age:measured in years

Qualitative data is:
Grouped/ Categorical eg. Preferred accomodation type (Budget, Tourist, Superior)

Categorical data (Qualitative) is:
 Nominal (name or number given to a category as a label)
 Ordinal (name or number implies ranking)

Numerical data (Quantitative) is:
 Discrete (whole or counting numbers)
 Continuous (infinite number of values eg. Age, Income)

A population is the :
Whole collection of things under consideration

A sample is a:
Portion of the poplulation selected for analysis

A parameter is a:
Summary measure that describes the characteristic of the population

A statisitic is a:
Summary measure computed that describes a characteristic of a sample.

Sources of data:
 Primary data
 Secondary data
 Census
 Experimental data
 Surveys

Non sampling errors:
 Coverage error
 Non response error
 Measurement error

Sampling error:
Chance differs from sample to sample

Measures of central tendancy:
 Mean (Average)
 Median (Middle value)
 Mode
 Trimmed Mean (cuts out extreme 5%)

Measures of spread:
 Range (Max  Min)
 Interquartile range (middle 50%)
 Varience (std dev around the mean)
 Std Deviation (square root of the varience)

Measures of shape: Skewness
 Symmetric distribution (median = mean)
 Right skewed (Tail to the right)
 Left skewed (Tail to the left)

Measures of shape: Kurtosis
 Positive Kurtosis: Data clusters more and have longer tails
 Negative Kurtosis: Data is less clustered and has shorter/ fatter tails

Box and whisker plots:
 Box (shows interquartile range)
 Line (median)
 Whiskers (highest and lowest value)
 Outliers
 Extreme outliers