Descriptive statistics offers a simple way to describe data, whereas inferential statistics take the findings a step further and allow us to come to a conclusion about our hypotheses. Descriptive statistics allow us to merely make conclusions of patterns that emerge from the data at present. Inferential statistics, on the other hand, allows us to make conclusions beyond the data we have analyzed.
• Descriptive statistics
Although descriptive statistics allow data to be summarized and described, we cannot make a conclusion related to an earlier hypothesis. The Habermas website (www.habermas.org/stat2f98.htm) gives the example of undertaking a survey about the gender composition and study attitudes of two school classes. The results could be used to describe issues that affect the particular members surveyed, but they could not be used to make generalized conclusions about other school classes because we cannot know whether the classes in the study are representative of all school classes or not.
• Inferential statistics
By using inferential statistics, you can be sure that your sample in a study is representative of the entire group that you wish to make a generalization about. You cannot simply do a survey at a local shopping mall and proclaim the results to be representative of all shoppers. Similarly, you cannot survey a women's movement with a majority from one particular ethnic group then claim the results to represent all ethnic groups. When trying to create inferential statistics from groups of people, the process of 'sampling' is important to ensure that the people that you actually survey are as representative of the wider group you wish to hypothesize about as possible.
• Descriptive statistics
Although descriptive statistics allow data to be summarized and described, we cannot make a conclusion related to an earlier hypothesis. The Habermas website (www.habermas.org/stat2f98.htm) gives the example of undertaking a survey about the gender composition and study attitudes of two school classes. The results could be used to describe issues that affect the particular members surveyed, but they could not be used to make generalized conclusions about other school classes because we cannot know whether the classes in the study are representative of all school classes or not.
• Inferential statistics
By using inferential statistics, you can be sure that your sample in a study is representative of the entire group that you wish to make a generalization about. You cannot simply do a survey at a local shopping mall and proclaim the results to be representative of all shoppers. Similarly, you cannot survey a women's movement with a majority from one particular ethnic group then claim the results to represent all ethnic groups. When trying to create inferential statistics from groups of people, the process of 'sampling' is important to ensure that the people that you actually survey are as representative of the wider group you wish to hypothesize about as possible.
