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Section 1 -
Learning from data
- Types of variable
- Qualitative data - take values from
a set of categories
- Nominal - no natural order
- e.g. colour, address
- e.g. colour, address
- Ordinal - natural order
- e.g. degree classification, place
in a competition
- e.g. degree classification, place
in a competition
- Nominal - no natural order
- Quantitative data - take values
on a numerical scale
- Continuous
- Discrete
- Continuous
- Data sets
- Univariate
- Multivariate
- Univariate
- Qualitative data - take values from
a set of categories
- Describing distributions
- Graphs
- Boxplots
- Histograms - show the frequencu
with which observations of
QUANTITATIVE variable fall in
specified intervals
- Scatter Plots
- Empirical Distribution Function -
show the proportion of observation
that fall below a specified value (uses
the indicator function.)
- Quantile-quantile plot - uses order statistics and
gives a comparison of two distributions
- Boxplots
- Statistics
- Location - describes where on the numerical scale the data tends to fall
- Mean
- Median - (resistant)
- Mode
- Quantiles - uses order statistics!
- Mean
- Shape - whether a
distribution is symmetric or
not
- Product moment correlation
co-efficient
- Yule-Kendall statistic
- Positive/Negative skew
- Product moment correlation
co-efficient
- Scale - describes how far the data is
spread across the numerical scale
- Standard Deviation
- Inter-quartile range
- Variance
- Range
- Standard Deviation
- Sample statistic - any quantity
calculated from a sample
- Location - describes where on the numerical scale the data tends to fall
- Graphs
- Association
- Graphically
- Scatter plot
- Scatter plot
- Numerically
- Covariance
- Correlation
- Covariance
- Graphically
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