Basic Concepts in Statistics

Differentiate between descriptive and inferential statistics. What information do they provide? What are their similarities and differences? Your answer should be 250 to 400 words.

Descriptive statistics are values that describe the characteristics of a sample or a population. Descriptive statistics allows a large amount of information or data to be used in order to come up with a summary of the data (Salkind, 2014). 

. For instance if you had a list of students at a school from the same grade and listed all their grades in differing subjects you could use descriptive statistics in order to find the average or mode of the kids grades. Descriptive statistics is able to take either a large sample or a population and turn the list of information, data set, into a summary that researchers can then use in different capacities such as predicting the grades of students across an age group.  If the researcher wanted to see what subject children excel more in then through the use of the grades and the differing subjects they would be able to find that information. Inferential statistics is different as it is the tools that are used in order to infer the results based on a sample to the population (Salkind, 2014). Inferential sometimes follows descriptive statistics as the next step in the process taking the small group that may have been used and applying the information to a larger group or population.  The inferential statistics allow researchers to make a kind of guess into how the summary that was created may apply to a larger population.  If researchers took a sample of a few different students from several schools in order to find grades in subjects they could then use the results to infer what the whole population may look like.

What is a population? What is a sample? How are they similar and how are they different? When would you use one or the other? Your answer should be 250 to 400 words.

A population according to Salkind (2014).  Is all the possible subjects or cases of interest.  So if a person wanted to know how good a soccer team was then they would use all individuals on the soccer team as the population when doing calculations.  While sample is a subset of a population (Salkind, 2014). It is much like its name describes and only a small portion of the total population. So in the soccer team you would take 10 players and this would be the sample. Both are representatives of the data that a person is trying to produce with one entailing all the subjects involved and the other only being made up of a portion.  When a population is relatively small such as the example of the soccer team then it is possible to use the entire population in the calculations being done. However when the population is larger such as looking at teen drug use then the population would include a size so big that it would be relatively impossible to look at all teens in the world. It would take too much time any money in order to do this. In this case a sample is pulled in order to represent the entire population while still getting the insight that a behavioral scientist is looking for. That way the scientist is able to pull a relatively small amount in comparison to the entire globe and is able to make inferences on who the results apply to the entire population of teens.

Salkind, Neil, J.(2014). Statistics for People Who Think They Hate Statistics. 5th Edition. Sage Publications.