Statistical reasoning is a theory that involves choosing and checking ingredients for a statistical problem. These ingredients include: data, a model, and a prior.  Statistical reasoning involves making interpretations based on sets of data, graphical representations, and statistical summaries. It can involve connecting one concept to another, such as understanding the relationship between the mean and standard deviation in a distribution.  Statistical reasoning can also involve learning to use statistics and/or probabilistic re-zoning to make decisions in situations where knowledge is... Show more

Statistical reasoning is a theory that involves choosing and checking ingredients for a statistical problem. These ingredients include: data, a model, and a prior. 

Statistical reasoning involves making interpretations based on sets of data, graphical representations, and statistical summaries. It can involve connecting one concept to another, such as understanding the relationship between the mean and standard deviation in a distribution. 
Statistical reasoning can also involve learning to use statistics and/or probabilistic re-zoning to make decisions in situations where knowledge is incomplete or the future unpredictable. 

Some examples of statistical reasoning include:
Probability using counting methods
Conditional probability
Permutations and factorial notation
Modeling data with a line of best fit
Mutually exclusive and non mutually-exclusive events
Modeling data with a curve of best fit
Independent events 

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