T-testanalysis in business research
Thereare many statistical tests that can be utilized in business research.T-test analysis is of these statistical tests. The approach has overthe past years emerged as one of most commonly used statisticalanalysis tool. The paper focuses on two sample t-test analysis whichis normally used to test the similarity or difference in mean valuesof two independent variables. In business research, the two samplet-test analysis can be used to test whether there are any significantdifferences in how male and females perceive a certain range ofproducts. The purpose of this paper is to investigate the use twosample t-test analyses in business research. The paper investigatesthe application of the approach in past business research and how thetest makes it possible for research questions to be answered.Additionally, the paper will discuss other statistical tests that canbe applied in business research, highlighting their role in research,their main components, limitations as well as interpretations.
Thetype of statistical test a researcher decides to use impacts theinterpretation of findings to a great extent. The nature of both theindependent and dependent variable impacts the choice of anappropriate statistical tool. Apart from the nature of the variables,the number of both the dependent and independent variables also hasan impact on the choice of the statistical test to be used by aresearcher (Nayak and Hazar, 2011). The current study takes anin-depth analysis of the application of t-test analysis and how itimpacts the findings and interpretation of the findings in research
Schou(2005) utilizes two sample t-test analyses to compare the learningoutcomes of business students in an online class environment andthose in a traditional class environment. He points out that due toeconomic constraints, learning institutions are increasingly offeringdistance learning options for various courses. The article arguesthat the success of online learning is important for theadministrations of the learning institutions, accrediting bodies aswell as the specific faculties offering the online courses. Tocompare the learning outcomes of the students, the author came upwith two hypotheses that were tested using two sample t-testanalysis. The first hypothesis was that there is no significantdifferences in the final examination mean score between students inthe traditional classroom setting and the online classroom setting.The second hypothesis that the author sought to test was that theoverall mean pre-test Survey of Attitudes toward Statistics (SATS)score is lower or equal to the overall mean post-test Survey ofAttitudes toward Statistics (SATS) score. A total of 31 participantstook part in the study with 16 participants being part of thetraditional class environment and 15 students being part of theonline class environment. The findings indicated that there was nosignificant difference in the learning outcomes of the two groups andthat students in the online class setting showed improved attitudecompared to those in the traditional class environment.
Elliset al (2009) also make use of t-test analysis in their study whichsought to investigate the impact of multitasking on the gradeperformance of business students. The authors argue that thetremendous growth of information technology has led to creation of astudent generation that believes in multitasking. They argue thatpast studies have revealed that multitasking negatively impact theability of the brain to process and interpret information. In thisstudy, a total of 62 participants were recruited. The participantswere allowed to multitask during a class session after which theywere given a quiz. Ellis et al (2009) sought to test 5 hypotheses.The first hypothesis was that there is no significant difference inthe mean score of students who were allowed to text and those who didnot text. The second hypothesis they sought to test was that there isno significant difference between the mean scores of female and malestudents. Another hypothesis was that there is no significantdifference in the mean scores of testing and non-texting femalestudents and that there is no significant difference in the meanscores of testing and non-texting female students.
Themean differences in the scores were investigated using an independentt-test. The variables that were investigated were the texting andnon-texting students as well the female and female students. Withregard to the first hypothesis, the study reports that there is asignificant difference in the performance of texting and non-textingstudents in a business class. However, there is no significantdifference in the performance of male and female students, anindicator that performance in a business class in not affected bygender.
Otherresearchers that utilized t-test analysis in the study are Chai andChen (2010) in their study, the researchers investigated the attitudeof consumers towards green products and the environment. They pointout that the rapid rate of economic growth around the globe has ledto the deterioration of the environment. They point out that the aimof their study is t investigate the attitudes of the two genderstowards green products and the environment and to investigate therelationship between the attitude towards green products and theenvironment. To compare the attitudes held by both the males andfemales with regard to green products and the environment, Chai andChen (2010) utilize the independent t-test. The authors proposed 5different hypotheses that they sought to test using the t-testapproach. The first hypothesis was that there is no significantdifference in the environmental attitudes of males and females. Thesecond hypothesis they proposed was that the attitudes of females andmales towards green products significantly differs. Anotherhypothesis was that there is a significant relationship betweenconsumer’s attitude towards government’s role and their attitudeon green products. The final hypothesis stated that there is asignificant relationship between the personal norm of consumers inenvironmental issues and their attitude on green products. Thefindings from the analysis revealed that there were no significantdifferences in attitudes of both males and females with regard to theenvironmental and green products green products.
Thetwo sample t-test analysis is normally used to test the similarity ordifference in mean values of two independent variables. It is thewidely used test in both business and non-business research. The useof t-test analysis involves testing the null hypothesis against thealternative hypothesis. The use of two sample t-test analysisrequires a number of background assumptions to be satisfied. Theseassumptions include the requirement that the population from whichthe sample is drawn from to have a normal distribution and that thestandard deviation of the population be equal (Elliot and Woodward,2007). Another assumption that the statistical test requires to besatisfied is that the samples should be randomly drawn from thepopulation and be independent of each other. Apart from that, thevariables of interest in t-test analysis should be random values. Oneof the advantages the approach offers is that it eliminates selectionbias. Additionally, the analysis can be conducted on a number ofsamples namely independent samples, paired samples as well as onesample.
Statisticaldata plays an important role in business decision making. There aremany statistical tools that businesses can utilize to come to theright decisions. The current study investigated the application oftwo-sample t-test analysis in business research. It was pointed outthat the two sample t-test analysis is normally used to test thesimilarity or difference in mean values of two independent variablesand that it is among the widely utilized statistical tests in theboth business and non-business research. The paper also discussedpast studies that utilized the approach, highlighting how theapproach was crucial in shaping the findings of the said studies. Ingeneral, the use of t-test in business research involves testing thenull hypotheses against the alternative hypotheses. Additionally, ituse requires a number of background assumptions to be satisfied.These assumptions include the requirement that the population fromwhich the sample is drawn from to have a normal distribution and thatthe standard deviation of the population be equal
Chen,T., & Chai, L. (2010). Attitude towards the Environment and GreenProducts: Consumers’ Perspective. ManagementScience And Engineering, 4(2),27-39.
Elliott,A., & Woodward, W. (2007). Statisticalanalysis quick reference guidebook.Thousand Oaks, Calif.: Sage Publications.
Ellis,Y., Daniels, B., & Jauregui, A. (2009). The effect ofmultitasking on the grade performance of business students. ResearchIn Higher Education Journal, 13(3),1-10.
Nayak,B., & Hazra, A. (2011). How to choose the right statisticaltest?. IndianJ Ophthalmol, 59(2),85. doi:10.4103/0301-4738.77005
Schou,S. (2005). A Study of Student Attitudes and Performance in an OnlineIntroductory Business Statistics Class. ElectronicJournal For The Integration Of Technology In Education,, 6(2),70-81.