Summary Statistics
- Created by: Cyn:)
- Created on: 21-02-14 18:18
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- Summary Statistics
- Types of variables
- Quantitative variable
- Continuous numerical variable.
- Ordinal variable - interval scale
- Categories that have an obvious order. E.g: Disease severity ( mild, severe, convalescent).
- Discrete variable
- discontinuous numericalvariable
- Example: Age as a whole number or number of cells in a culture.
- Categorical variable
- Sometimes described as nominal
- Non - numerical values
- Dichotomus- 2 categories such as female or male.
- Polytomous- more than 2 categories. E.g: Blood type or types of birds.
- Quantitative variable
- SAMPLE: collection of individuals or things on which we measure or more variables.
- POPULATION: total collection of individuals or things from which we have drawn the sample.
- Measures of CENTRAL TENDENCY
- is a central value or a typical value for a probability distribution.[1] It is occasionally called anaverage or just the center of the distribution.
- Apart from Average/mean. The position on the X-axis can be describe by mode or median as well.
- MODE: the class with the highest frequency.
- MEDIAN: middle value when in chronological order.
- Apart from Average/mean. The position on the X-axis can be describe by mode or median as well.
- is a central value or a typical value for a probability distribution.[1] It is occasionally called anaverage or just the center of the distribution.
- Measures of dispersion
- scatter of data values
- If values are all the same there is NO DISPERSION.
- If the values are widely scattered then GREATER DISPERSION.
- scatter of data values
- Parametric and non-parametric.
- Parametric method- oldest method. May not be appropriate for biological data.
- This method makes assumptions that may not be true.
- Non- Parametricmethods: new method. NOT based upon stringent assumptions.
- More suitable for processing biological data. Generally, simpler to use since they avoid long and repetitive calculations,
- Parametric method- oldest method. May not be appropriate for biological data.
- Types of variables
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