COMMERCE 2QA3 Study Guide - Final Guide: Time Series, Box Plot, Squared Deviations From The Mean
28 Jun 2018
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Histograms
Height of bars describes "shape" of data. Decide how wide to make the bins - if there are n data points, use
Determine the count for each bin and decide where to place value that land on the enpoint of a bin. Standard rule
is to place values in the higher bin.
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Stem-and-Leaf Displays
Similar to histograms but also give individual values. Example: Display 21, 22, 24, 33, 33, 36, 38, 41
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Before making a histogram or SLD, the Quantitative Data Condition must be satisfied where data values are of a
quantitative variable whose units are known.
Shape
Shape of distribution is described in terms of modes, symmetry, and whether there are gaps or outlying values.
Modes
Peaks or humps in histogram. These can be unimodal, bimodal, or multimodal. When the mode is
unclear and uniform, there is a uniform distribution.
Symmetry
Closeness to a mirror image.
Thin ends of distribution are tails. If one tail stretches out further than the other, the distribution is
skewed towards that side.
Outliers
Values that stand away from body of distribution.
Centre
Mean is natural symmetry and the centre point of a unimodal and symmetric distribution.
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Median should be used when distributions skewed, gapped, or has outliers, as the value splits the histogram into
two equal areas. This number is resistant because it is unaffected by unusual distribution shapes. Mean = median
in symmetric distributions.
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Spread
When data varies, a measure of centre becomes ineffective.
Range is the difference between the extremes. It is a single value and is NOT resistant to unusual distributions.
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Quartiles frame the middle 50% of the data. The InterQuartile Range [IQR] is the difference between two quartiles.
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The average of the squared deviations of the values of variable y from the mean is the variance and is denoted by
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Sample variance =
Population variance =
Taking the square root of the variance gives us the standard deviation, denoted by s.
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Coefficient of variation measures how much variability exists compared with the mean. It is the ratio of standard
deviation to the mean.
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Displaying and Describing Quantitative Data
September 10, 2017
11:53 AM
Statistics Page 1
Document Summary
Determine the count for each bin and decide where to place value that land on the enpoint of a bin. Standard rule is to place values in the higher bin. Decide how wide to make the bins - if there are n data points, use. Before making a histogram or sld, the quantitative data condition must be satisfied where data values are of a. Similar to histograms but also give individual values. Example: display 21, 22, 24, 33, 33, 36, 38, 41 quantitative variable whose units are known. Shape of distribution is described in terms of modes, symmetry, and whether there are gaps or outlying values. When the mode is unclear and uniform, there is a uniform distribution. If one tail stretches out further than the other, the distribution is skewed towards that side. Values that stand away from body of distribution. Mean is natural symmetry and the centre point of a unimodal and symmetric distribution.
