Normal_ID: Normal Prior Distribution Identifier
In rnorouzian/BayesianforL2: Introduction to Bayesian Thinking for L2 Researchers

Description Usage Arguments Details Value Author(s) Examples

Uses the subject matter researcher's knowledge to generate a corresponding Normal prior distribution.

1	Normal_ID(Low, High, Cover = NULL)

`Low`	researchers LOWEST value for the parameter.
`High`	researchers HIGHEST value for the parameter.
`Cover`	coverage for the Low and High values provided.

solves to provide graphical and textual information about an appropriate Normal prior distribution.

Provides graphical as well as full textual description of a suitable Normal distribution for researcers based on their knowledge about how High or Low the parameter has been found in the literature. Also, helps researcher to revise their prior by issuing various messages.

Reza Norouzian <rnorouzian@gmail.com>

# Suppose a researcher needs a Normal prior for a Cohen d effect size that in
# his/her view can't be less than -3 and more than +3. The researcher believes
# these two limit values cover 95% of all possible values that this parameter
# can take:


 Normal_ID (Low = -3, High = 3, Cover = '95%')



# User can also use any value that is between 0 and 1 for the argument
# cover without using percentage sign:



Normal_ID (Low = -3, High = 3, Cover = 95)