BUSS1020 Lecture Notes - Lecture 3: Interquartile Range, Fidelity Investments, Confounding
5 Jun 2018
School
Department
Course
Professor
To describe the properties of central tendency, variation, and shape in numerical data.
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To construct and interpret a boxplot
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To compute descriptive summary measures for a population
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LO:
The central tendency is the extent to which all the data values group around a typical or central value.
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The variation is the amount of dispersion or scattering of values around the central value
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The shape is the pattern in the distribution of values from the lowest value to the highest value.
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Summary of Definition:
Central Tendency
1.
Mean:
3. Numerical Descriptive Measures
Wednesday, 14 March 2018
10:53 AM
Textbooks Page 1
Middle value in an ordered array (smallest to largest) then halved to find median
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Not affected by extreme values --> can use median where extreme values are present
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daily asset return for most assets and most time periods is 0 %
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income in the US for 2012 was $39,333
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house price in Sydney in 2012 was $641,037
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Example:
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The Median:
Value that occurs most often
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Not affected by extreme values
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Used for either numerical or categorical (nominal) data
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There may be no mode
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There may be several modes
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Mode:
Mean= generally used, unless extreme values (outliers) exist.
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For example, median home prices may be reported for a region; it is less sensitive to outliers.
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The median = often used, since the median is not sensitive to extreme values.
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In some situations it makes sense to report both the mean and the median.
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The mode = most frequent observation. The data set may have more than one mode. Usually reported for discrete data
only
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Which Measures to Choose:
Geometric mean = Used to measure rate of change of a variable over time
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Use geometric mean instead of arithmetic mean
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Geometric rate of return = used to calculate the average rate per period on an investment that is compounded over
multiple periods. The geometric mean return may also be referred to as the geometric average return.
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Note = have to complete calculations step by step as GCD cannot do it all together
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Geometric Mean
Textbooks Page 2
Textbooks Page 3
Document Summary
To describe the properties of central tendency, variation, and shape in numerical data. To compute descriptive summary measures for a population. The central tendency is the extent to which all the data values group around a typical or central value. The variation is the amount of dispersion or scattering of values around the central value. The shape is the pattern in the distribution of values from the lowest value to the highest value. Middle value in an ordered array (smallest to largest) then halved to find median. Not affected by extreme values --> can use median where extreme values are present. Example: daily asset return for most assets and most time periods is 0 % income in the us for 2012 was ,333 house price in sydney in 2012 was ,037. Used for either numerical or categorical (nominal) data. Mean= generally used, unless extreme values (outliers) exist.
