**Independent -means t-test:**

used when there are two experimental conditions and different participants were assigned to each condition. also referred to as the independent-measures or independent-samples t-test

**Dependent-means t-test:**

used when there are two experimental conditions and the same participants took part in both conditions of the experiment. also referred to as the matched-pairs or paired-sample t-test.

calculating with standard error* : small standard error=most samples similar means

**Assumptions of the t-test**

- The sampling distribution is
*normally distributed*. In the dependent t-test this means that the sampling distribution of the differences between scores should b normal. not the scores themselves. - The independent t-test, because it is used to test different groups of people, also assumes:
*homogeneity of variance*(variances in these populations are roughly equal), scores are independent (because they come from different people).

* Standard error: the standard deviation of sample means. It is a musure of how representative a sample is likely to be of the population. As sample get large (greater than 30), the sampling distribution has a normal distribution with a mean equal to the population mean(=central limit theorem)

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