There is one other result worth noting here, and that’s Levene’s Test for Equality of Variances. Step 2: Calculating the t-test statistic for an independent samples t-test. It’s reporting an F value of 2.900 and a significance value of .100. It’s an assumption of the independent samples t test that both samples have the same variance. "Here is a summary of the results:" So what I want you to do, is pause this video, and conduct a two sample T test here. t-Test for the Significance of the Difference between the Means of Two Independent Samples This is probably the most widely used statistical test of all time, and certainly the most widely known. The independent two-sample t-test is used to test whether population means are significantly different from each other, using the means from randomly drawn samples. Both samples are simple random samples from their respective populations. 5. It is most often used to determine the difference between groups that have received some kind of treatment. 4. Independent Samples T-Test Output. There is an independent samples t-test (this example) that compares two samples to each other. Thus, the treatment groups do not have overlapping membership and are considered independent. An independent sample t-test determines the difference between two groups with different participants in each group. Each individual in the population has an equal probability of being selected in the sample. And let's assume that we are working with a significance level of 0.05. A t-test is a means of comparing two means. A t-test may be used to evaluate whether a single group differs from a known value (a one-sample t-test), whether two groups differ from each other (an independent two-sample t-test), or whether there is a significant difference in paired measurements (a paired, or dependent samples t-test). : Any statistical test that uses two samples drawn independently of each other and using t-distribution, can be called a 'two-sample t-test'. NOTE: There are three types of t-tests. It is aimed for testing if the mean of the value one has targeted is equal to the mean of two independent populations, e.g., Testing whether the average weight of Class 5 boy students is different from Class 5 girl students. Requirements. An independent samples t-test is typically used when each experimental unit, (study subject) is only assigned one of the two available treatment conditions. It is simple, straightforward, easy to use, and adaptable to a broad range of situations. There is no relationship between the individuals in one sample as compared to the other (as there is in the paired t -test). The two samples are independent. Further Information. Two independent samples; Data should be normally distributed; The two samples should have the same variance; Null Hypothesis Levene’s Test checks this assumption. An independent samples t-test is the simplest form a “between-subjects” analysis. Well, this depends on Levene's test for equal variances which tests the aforementioned homogeneity assumption. Comparing Two Means – Two Independent Samples T-test LO 4.38: In a given context, determine the appropriate standard method for comparing groups and provide the correct conclusions given the appropriate software output. There is the one sample t-test that compares a single sample to a known population value. Note that we have two lines of t-test results: equal variances assumed and equal variances not assumed. #2 – 2-Sample T-Test. 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