Difference between Descriptive and Inferential Statistics

Difference between Descriptive and Inferential Statistics

 

Descriptive Statistics

Use descriptive statistics to summarize and graph the data for a group that you choose. This process allows you to understand that specific set of observations

Descriptive statistics frequently use the following statistical measures to describe groups:

 

       I.          Central tendency: Use the mean or the median to locate the center of the dataset. This measure tells you where most values fall.

     II.          Dispersion: How far out from the center do the data extend? You can use the range or standard deviation to measure the dispersion. A low dispersion indicates that the values cluster more tightly around the center. Higher dispersion signifies that data points fall further away from the center. We can also graph the frequency distribution.

   III.          Skewness: The measure tells you whether the distribution of values is symmetric or skewed. See: Skewed Distributions

there are other descriptive analyses you can perform, such as assessing the relationships of paired data using correlation and scatterplots.

inferential          

For inferential statistics, we need to define the population and then devise a sampling plan that produces a representative sample. The statistical results incorporate the uncertainty that is inherent in using a sample to understand an entire population. The sample size becomes a vital characteristic. The law of large numbers states that as the sample size grows, the sample statistics (i.e., sample mean) will converge on the population value.