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What is a t-test in quantitative research?
A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. A t-test is used as a hypothesis testing tool, which allows testing of an assumption applicable to a population.
How do you know if it is a dependent or independent t-test?
How are dependent and independent samples different?
- If the values in one sample affect the values in the other sample, then the samples are dependent.
- If the values in one sample reveal no information about those of the other sample, then the samples are independent.
What is a Dependant t-test?
The dependent t-test (also called the paired t-test or paired-samples t-test) compares the means of two related groups to determine whether there is a statistically significant difference between these means.
What do you need to know about the t test?
The t-test is a parametric test of difference, meaning that it makes the same assumptions about your data as other parametric tests. The t-test assumes your data: are (approximately) normally distributed.
What are assumptions made when conducting a t-test?
The assumption for a t-test is that the scale of measurement applied to the data collected follows a continuous or ordinal scale, such as the scores for an IQ test. The second assumption made is that of a simple random sample, that the data is collected from a representative, randomly selected portion of the total population.
What is the formula used to calculate the t-test?
Statistical Analysis of the T-Test. The formula used to calculate the test is a ratio: The top portion of the ratio is the easiest portion to calculate and understand as it is the difference between the means or averages of the two samples.
What are the different types of TB tests?
There are two types of tests for TB infection: the TB skin test and the TB blood test. A person’s health care provider should choose which TB test to use. Factors in selecting which test to use include the reason for testing, test availability, and cost.