IMPORTANT NOTE REGARDING WORD LIMIT REQUIREMENTS:
Please note that each and every assignment has its own word limit. 
A population is the subject of the study which is selected from a large group of cases that the researcher is interested in studying. For example, if the researcher wanted to study the effect of diabetes on a community, the population would consist of all the people within a targeted community who are diabetic. A sample is a subset of the population for example, within the community of diabetic people, the sample will be females who became diabetics after pregnancy. In terms of analyzing data, a statistic is used when characterizing a sample and a parameter is used when characterizing a population. For example, when examining how many people within the community have diabetes the parameter would be 80% of the population is diabetic and when examining how many females became diabetic after pregnancy, the statistics would be 50% of the sample is diabetic (Corty, 2016).
A descriptive statistic summarizes data, for example, 80% of the population that is diabetics, 50% are male and 30% are female. Whereas, inferential statistic draws a conclusion about the population. For example, instead of saying the average diabetic in the sample of females after pregnancy within a community is 50%, and inferential statistics would state, females who give births on average, have a diabetic percentage of 50%. The ability to differentiate between the terms is important because it makes communication easier and effective when presenting data and the knowledge prevents misinterpretation and errors of the data. For example, if there is an E.coli outbreak within a community, and the data presented was misinterpreted, this could cause the source of the outbreak to go unnoticed and caused death within the community (Corty, 2016).
Reference
Corty, E. (2016). Using and interpreting statistics: A practical text for the behavioral, social, and health sciences (3rd ed.). New York, NY: Macmillan Learning.
 
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