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Continuous Random Data, Non Random Variables - Coggle Diagram

- - - - summarising the information by using its 'probability distribution'
        
        Continuous Probability Distributions
        
        F Distribution
        
        Used to compare the difference between population variances
        
        T Distribution
        
        Is used when the population sample is below 30
        
        Is used when the standard deviation is not known
        
        Similar to normal distribution but the shape is flatter and shorter
        
        The degrees of freedom define the shape of the t curve
        
        Outside the normal distribution
        
        Skewness
        
        A measure of data symmetry
        
        0 skewness
        
        Positive skew
        
        1 more item...
        
        Negative skew
        
        1 more item...
        
        Kurtosis
        
        'Peakedness' or 'tail fatness'
        
        The wider the curve = the larger the standard deviation
        
        A list of all possible outcomes
        
        The sum of all probabilities must equal 1
        
        0 = impossible
        
        1 = Certain
        
        Presented graphically
  - - - Whole numbers
- - - - P value
        
        From the Z score you can then identify the corresponding probability distribution
        
        Using The Standard Normal Distribution Tables
      - How far away the data point is from the mean (by standard deviation)
    - - Measured in units of the standard deviation
      - Has a mean of 0 and a standard deviation of 1
  - - - Most probabilities clustered at the mean