Running head: ANOVA TEST AND T-TEST 3
Running head: ANOVA TEST AND T-TEST 1
ANOVA TEST AND T-TEST
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ANOVA is a statistical method used to measure the potential differences in the scale level of a dependent variable by a nominal-level variable. For instance, the ANOVA test can be used to evaluate the potential differences in abnormality test scores between two countries. The ANOVA test is generally used in three main ways, which are one-way ANOVA, two-way ANOVA, and N-way ANOVA. One-way ANOVA means that the variables have only one independent variable. For instance, the difference in abnormality can be evaluated in one country; the country can have its categories to compare from. The two-way ANOVA refers to the evaluation of variables using two independent variables. The two way ANOVA can be used to evaluate the difference in abnormality test and gender in a country. Lastly, the N-way is where the researcher uses more than two independent variables. For instance, the differences in abnormality can be evaluated by country, ethnicity, age group, and gender.
The T-test is a statistical technique used to compare the difference between two different sample means. The test is used to show how significant these differences are. The samples means have to be from a normally distributed population which have unknown variances. This means that the T-test is an evaluation of the difference between sample means when the variable of more than one normal distribution is unknown. The T-test mostly assesses the degrees of freedom, the t-statistic, and the t- distribution to measure the difference in probability between populations. To conduct a test with more than two variables, then one would consider using the ANOVA test, z-test, chi-square or the f-test as an analysis of variances.
References
Adams, R. J., & Khoo, S. T. (1993). Quest: The interactive test analysis system.
Cuevas, A., Febrero, M., & Fraiman, R. (2004). An anova test for functional data. Computational statistics & data analysis, 47(1), 111-122.
Norušis, M. J. (2006). SPSS 14.0 guide to data analysis. Upper Saddle River, NJ: Prentice Hall.