Descriptive And Inferential Statistics
Statistics are important in the field of psychology because they allow researchers to analyze information, illustrate research results, and organize data. Statistics provides a unique perspective on understanding data and interpreting information in charts and graphs. It can be difficult for anyone to collect and fully comprehend large amounts of data. The use of statistics in the research process enables researchers to examine all of the data at the same time. Statistics are classified into two types of statistical methods: descriptive statistics and inferential statistics. Descriptive statistics condense information about the research, whereas inferential statistics draw conclusions from the research (Aron et al., 2009). If researchers did not have statistics as another technique for not only understanding data but also confirming their theories during their research, they would be at a disadvantage.
Statistics Function
Statistics is not only used in mathematics; it is also an important tool in the field of psychology. Statistics assist in gathering various results and information that is required to assist others in providing a better result for the test that he or she may have taken. A psychologist will use two types of statistics to obtain and present the necessary results: descriptive and inferential statistics (Cherry, 2013). Descriptive statistics paint a picture of what happened during the test. This test typically provides information such as the mean, median, and mode of the test results or the average of where a person ranks on that test (Net Industries, 2013). Inferential statistics are derived from the results of any tests that he or she may have taken. These analyses are generated directly from the test to determine how the patient performed, allowing us to better assist the patient. When the statistics of the results are provided, a person can better understand the results to show what help is required or not required, and he or she can get help to resolve the situation in only the areas where he or she can help himself or herself completely.
Statistics that are descriptive
Descriptive statistics are precisely what their name implies. This type of statistic merely provides a summary of the basic characteristics of the data collected. The use of descriptive statistics is an important part of the research to avoid distorting data or losing important details. “Each descriptive statistic condenses a large amount of data into a more concise summary” (Trochim, 2006, para. 3). Measuring only the GPA of a student’s grades does not provide information about the type of course, the student is enrolled in; rather, it presents the average of a student’s total grades. The United States Census Bureau employs descriptive statistics to describe the ethnic groups in our country. Descriptive statistics allow us to present data in a simplified format that is easily understood. Tools for understanding and displaying descriptive statistics data include frequency distribution in a table, bar graph, histogram, or bar chart, as well as percentages.
Statistical Inference
Inferential statistics, as opposed to descriptive statistics, are based on drawing a conclusion, or inference, from statistical data generated during testing rather than purely informative statistics. This means that the data’s numbers are merely a means to an end in proving a point. According to Statistics for Psychology, “inferential statistics enable researchers to make inferences about a large group of individuals based on a research study in which a much smaller number of individuals participated” (Aron et al., 2009, p. 2). However, for statistics like these to work, some logical measurement involving the scope of frequency or trend generation must already exist. The foundation of the inference is created by using the mean to find a high point in a trend or the mode to find the highest frequency of a specific variable and then correlating that variable to either a separate parallel or perpendicular trend. Inferential statistics are frequently used to address a problem and imply a corrective course of action that would either offset or positively reinforce an action that would continue a trend.
Relationship
Working together, descriptive and inferential statistics can help to explain the information and data gathered. Averaging the SAT scores of everyone in the United States, for example, would not be considered practical. Using each score to calculate an exact mean would take too much time and effort. It would be more practical to take a sample of 5000 test results, 100 from each state, and find the mean of the scores. Inferential statistics are used to describe this type of sampling. Descriptive statistics would then allow one to graph or draw a representation of the results to help find patterns between the states that scored higher and how far each state was from the country’s collective mean. Descriptive statistics do not allow for any additional conclusions to be drawn from the data presented in order to test a hypothesis, such as the average SAT score of 1050. Based on the descriptive statistics gathered, one could infer that the average SAT score could be expected to be 1050 using inferential statistics.
References
Aron, A., Aron, E. N., & Coups, E. J. (2009). Statistics for psychology (5th ed.). Upper Saddle River, NJ: Pearson/Prentice Hall.
Cherry, K. (2013). Net Places – Psychology. Retrieved from http://www.netplaces.com/psychology/how-psychologists-know-what-they-know/the- essential-role-of-statistics.htm
Net Industries. (2013). Statistics in Psychology. Retrieved from http://psychology.jrank.org/pages/612/Statistics-in-Psychology.html
Trochim, W. M. K. (2006). Descriptive Statistics. Retrieved from http://www.socialresearchmethods.net/kb/statdesc.php
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Question 
This worksheet provides you with experience in calculating (by hand or using Excel®) formulas from the weekly readings.
Descriptive And Inferential Statistics
Using these formulas and performing these calculations provides you with an understanding of how and why statistical formulas work and what they mean. This worksheet also provides you the opportunity to interpret results in the context of specific problems, which assists you in critically evaluating current research in your field.