The Science discipline is subjective and some authors may provide results that just to satisfy their studies. We, the users of science should be careful while applying author’s knowledge in the studies. There is the importance of examining the hypothesis, results, and experiment conduct by the author. The examination should consider the structure of the report, argument or the main idea, conclusion, and tone of the author.
In this article, the author gives an explanation of the application of the statistical significance testing. However, the author, Carver (1993) biased as he gives his opinion only throughout the study. He never demonstrated any opposing studies to test the statistical significance. Since the author expresses his opinion, the results are based only on the one-way argument. Further, the tone of the article seems powerful and defensive.
Delegate your assignment to our experts and they will do the rest.
I disagree with the Carver's idea to skip the statistical significance testing as I have seen it increase the validity of the study. To proof the validity of a study, there is the importance of conducting the statistical test. However, this does not necessarily mean that all studies with statistical significance test are meaningful. Some scholars support their researchers with more than one tool and perform a comparative study to prove their values.
Though, I tend to agree with the concept of study replication. As indicated before, statistical testing can be subjective especially author is expressing his opinion. Therefore, using more repetition or replication will test a scenario and also test a situation that occurs often.
If I was the author, I would prefer the use of replication. In my view, it is a scientific principle that conducting an experiment that has ever been done before, the results should be the same. In cases where the results of the latter experiment differ, then the procedure followed is wrong.
Reference: Carver, R. P. (1993). The Case Against Statistical Significance Testing, Revisited. The Journal of Experimental Education, 61(4), 287-292
Lieber gives an article that is easy to read and well structured. Further, every point is supported with well-developed ideas.
I agree with your opinion and accept the bias in the Carver’s article. It is understandable that most of the methods applied need to be changed. For instance, the impact of sample error and size the studies. I had to go through the article multiple times to understand how the author has addresses significant statistical test. However, I objected that there need for changes. Since I was interested with the topic of this article, I ensured that I paid close attention to understand every concept. As I expressed Carver’s opinion and argument in the article, he should be able to proof his results through a scientific method or a comparative study. For a study to be valid, it should present two opposing viewpoints, arguments, the pro and cons, any other related research. In my opinion, Carver should understand that in scientific research, the author should not be “selfish” in expressing opinions. As an author, one should consider other scholars view on similar topics either in support or against your article.
Reference: 2. Lieber, R. L. (1990). Statistical Significance and Statistical Power in Hypothesis Testing. Journal of Orthopedic Research , 8(2), 304-309.
With this, the two articles have clearly demonstrated some of the "corrupted" scientific methods in researchers. Therefore, all that can be hoped for the reader is the ability to distinguish articles that have added: "statically" in form of "significant" at the expenses of testing statistical significance. Carver’s article is a perfect example how the argument tone of the author can affect the position of his opinion and also eliminate the statistical significance testing. It is clear that Carver’s (1978) argument and defensive tone is the best for scientific research. In such a study, the author should support his opinion after analyzing the points against the topic.
References
Carver, R. (1978). The case against statistical significance testing. Harvard Educational Review , 48 (3), 378-399.
Carver, R. P. (1993). The Case Against Statistical Significance Testing, Revisited. The Journal of Experimental Education, 61(4), 287-292
Lieber, R. L. (1990). Statistical Significance and Statistical Power in Hypothesis Testing. Journal of Orthopedic Research , 8(2), 304-309.
