Member-only story
Difference between Descriptive and Inferential Statistics –Statistics for Machine Learning
To gain knowledge about seemingly haphazard situations, statisticians collect information for variables, which describe the situation. But before we differentiate between Descriptive and Inferential Statistics, Lets define common terms in statistics.
Common Terms in Statistics
A variable is a characteristic or attribute that can assume different values.
Data are the values (measurements or observations) that the variables can assume. Variables whose values are determined by chance are called random variables.
Suppose that an insurance company studies its records over the past several years and determines that, on average, 3 out of every 100 automobiles the company insured were involved in accidents during a 1-year period. Although there is no way to predict the specific automobiles that will be involved in an accident (random occurrence), the company can adjust its rates accordingly, since the company knows the general pattern over the long run. (That is, on average, 3% of the insured automobiles will be involved in an accident each year.)
A collection of data values forms a data set. Each value in the data set is called a data value or a datum.
