distribution functions of random variables

Inferential statistical methods use sample data to make predictions about
the values of useful summary descriptions, called parameters, of the population
of interest. parameters as known numbers. This
is artificial, since parameter values are normally unknown or we would not
need inferential methods. However, many inferential methods involve comparing
observed sample statistics to the values expected if the parameter
values equaled particular numbers. If the data are inconsistent with the particular
parameter values, the we infer that the actual parameter values are
somewhat different.Inferential statistical methods use sample data to make predictions about
the values of useful summary descriptions, called parameters, of the population
of interest. parameters as known numbers. This
is artificial, since parameter values are normally unknown or we would not
need inferential methods. However, many inferential methods involve comparing
observed sample statistics to the values expected if the parameter
values equaled particular numbers. If the data are inconsistent with the particular
parameter values, the we infer that the actual parameter values are
somewhat different.Inferential statistical methods use sample data to make predictions about
the values of useful summary descriptions, called parameters, of the population
of interest. parameters as known numbers. This
is artificial, since parameter values are normally unknown or we would not
need inferential methods. However, many inferential methods involve comparing
observed sample statistics to the values expected if the parameter
values equaled particular numbers. If the data are inconsistent with the particular
parameter values, the we infer that the actual parameter values are
somewhat different.