2 : SAMPLING

1. Data is classified into 2 general
    categories : attributes & variables.
    When using attribute data, the
    focus is on learning about 1 or
    more specific non-numerical
    characteristics of the population
    being sampled. Examples of
    attributes are : red/green, yes/no,
    small/medium/large.

2. Confidence is the probability that
     the actual population value being
     estimated will be contained
     within the precision interval of
     our estimate.

3. The precision interval represents
     the total amount of sampling
     error that you should expect for
     any specific sample size.

4. Three factors to determine the
     sample size :
   (A) the desired confidence level,
         which determines the value of 
          Z, critical value of the  
          standardize normal
          distributions.
    (B) the acceptable sampling error
    (C) the standard deviation