There are strengths and weaknesses associated with statistical testing. For this discussion, begin by reviewing the various methods of statistical testing presented in your textbook (i.e., t-tests, ANOVA, chi-square, and f-tests). Then, keeping these methods in mind, read the following quotes: Based on the above quotes, along with this week’s assigned readings and Instructor Guidance, discuss why statistical testing is important in research.
There are strengths and weaknesses with statistical testing along with which techniques you use for which data. It’d important to use the correct statistical testing technique for the data and outcome for which you are looking for from the data. Chi-square test can test the associations between the variables which provides this testing an advantage (Lind, Marchal, & Wathen, 2017). However, the disadvantage to the Chi-square test is that it doesn’t provide the strength of the relationship (Lind, Marchal, & Wathen, 2017). Chi-square is never negative values and is always positively skewed (Lind, Marchal, & Wathen, 2017). ANOVA stands for analysis of variance and is the immediate comparisons of numerous populations means (Lind, Marchal, & Wathen, 2017). The f-tests are used by the ANOVA to test the equality of the mean (Lind, Marchal, & Wathen, 2017). A disadvantage to an f-test is that it can’t use negative values (Lind, Marchal, & Wathen, 2017). A contingency table is used to test if two behaviors or features are related. The sign test is used to display a positive or negative sign for the difference between two related observations (Lind, Marchal, & Wathen, 2017). If there is no difference than zero is logged and that person would be removed from the study. The advantage is that the sign test looks to have a study with participants that are not logged as a zero (Lind, Marchal, & Wathen, 2017). The Kruskal-Wallis test is used for independent populations meaning that each sample of populations must not influence the response of the other sample populations (Lind, Marchal, & Wathen, 2017). “Statistical analysis in cases involving small numbers can be particularly helpful because on many occasions intuition can be highly misleading.”—Sandy Zabell,Statistics: A Guide to the Unknown (3rd ed.)(1989). I enjoy this quote as statistical analysis with small numbers can have outcomes that are unpredictable based off of human’s instincts without the data or about the data before the analysis is completed. We all have our own opinions on what is happening at what we are statistically testing but until the research and analysis into those statistics are completed our instincts can be completely wrong and misleading.
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2017).Statistical techniques in business and
.(17th ed.). Retrieved from http://connect.mheducation.com/class/
According to the authors Taeger and Kuhnt, “Hypothesis testing aims at a decision on whether or not a hypothesis on the nature of the population is supported by the sample” (2014, pg.3). Statistical testing is a process that yields results to help determine whether or not a hypothesis is reasonable or valid. One way to run a hypothesis test on a population without having to test the entire population is to test a sample of that population. Working with a sample population can be advantageous for a researcher, and often, a researcher will work with two sample populations. For example, if a study is being done on a new drug, the researcher may want to set up a sample population taking the new medication alongside a sample population taking a placebo. When the studies are concluded, by utilizing two-test hypothesis methods, such as t-test and f-test, a researcher can determine whether or not the new medication had positive results or not. Many studies will have a control group, so comparing two populations can be very beneficial.
“In a world with amazing amounts of statistics and demographics available, If you don’t utilize foresight, statistics, demographics, projections, and predictions the competition will.”—Akutra-Ramses Atenosis Cea. I think this is a great quote with a powerful message. Statistics, data, and information are heavily utilized by business to gain any advantages possible over the competition. This quote is stating if you are in business and not using statistics; you can count on your competition using it and gaining an edge on you.
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2017). Statistical techniques in business and economics (17th ed.). Retrieved from http://connect.mheducation.com/class/
Taeger, D., & Kuhnt, S. (2014). Statistical Hypothesis Testing with SAS and R (Vol. First edition). Chichester, West Sussex: Wiley. Retrieved from http://search.ebscohost.com.proxy-library.ashford.edu/login.aspx?direct=true&db=edsebk&AN=686069&site=eds-live&scope=site
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