Any student who pursues a course in psychology has to conduct a statistical analysis at any point in their school life. The two types of statistics are descriptive and inferential. Descriptive statistics is always easy to deduce. Descriptive statistics includes the mean, mode, medium, and range. On the other hand, inferential statistics are compound and have different interpretations. More to the point, descriptive statistics usually describe a particular group while inferential statistics draw conclusions about a larger group of people. Inferential statistics works best when the researcher draws samples from a random population. In inferential statistics, the researcher must come up with both the null and alternative hypothesis. Moreover, when researchers write their report, they should make data results flow to make the reader understand the research data. Inferential statistics are the most difficult to understand, and researchers have to make the readers work easy. The paper discusses how a researcher can convey his or her data to make the reader make the right inference. More so, it explains how a reader can interpret research data the wrong way.
The reader of a research topic can take the interpretation of data the wrong way if the researcher fails to translate their statistics into a manner that is understandable. The researchers should enter the fields in the statistics correctly and add appendixes if possible to make the data more comprehensible. More to the point, the reader can take the results the wrong way if the researcher does not maintain consistency throughout his or her work. As well, the reader may fail to understand the research if the researcher includes misleading questions, margins of error, and incomplete interpretations. Again, the relevance of information is mandatory in any study. If not, the reader may interpret the data in a wrong way. Drotar (2009) affirms that data should be relevant to statistical assumption. Moreover, the reader can take the data the wrong way if the researcher does not organize and focus on the data flow.
The researcher can be sure that they convey data in a way for the reader to make the right inference if he or she does not make the research too complicated. Drotar (2009) articulates that the researchers should take the reader through a systematic analysis of their data and results. The researcher should utilize graphics and tables. Besides, Drotar (2009) puts forward that the information in the graphs and tables should not be redundant. More so, the researcher should put additionally and detailed explanations to the graphs and tables to convey the data in an understandable manner. More so, the author indicates that that the researchers should describe the rationale for their choice of statistics in a regression analysis. Drotar (2009) asserts that researchers should conduct statistical assessments that have clinical significance. Apparently, the data results should be at par with the study.
In summary, data usually presents the foundation for the conclusions of any research. Consequently, when a researcher wants to make the data results of the research to flow, they should calculate statistics that they know how to use. Besides, researchers should not interpret data results, which they do not fully understand. The reason is that there are minimal chances that the reader can fathom the data if the researcher does not know what he or she writes. Most importantly, the researcher should consider the type of audience that they want to read the research. They should ensure that the readers could understand the statistics. The researcher should make both a casual reader and an experienced reader comprehend the subject of the research. Overall, inferential statistics help researchers to know if their data shows a relationship with their research.
Drotar, D. (2009). Editorial: How to Write an Effective Results and Discussion for the Journal of Pediatric Psychology. Journal of Pediatric Psychology, Vol. 34, Issue 4.
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