What determines if two sets are significantly different from each other?
The Students T-test (or t-test for short) is the most commonly used test to determine if two sets of data are significantly different from each other. A wonderful fact about the Students T-test is the derivation of its name. You can use an unpaired t-test on paired data without a negative consequence.
Can you compare vectors of different dimensions?
If the vectors are homogeneous, for example, images of different dimensions, then another approach is possible to compare them. If the feature vectors varying in length you can apply some linear or nonlinear transformation to obtain vectors equal in length.
How to test if two data sets are statistically different?
These correspond to measurements on the same thing being studied. Each of the two data sets has N number of points. Each point in each data set has an associated error, which can be assumed to be Gaussian standard deviation. What I want to know is the following: how do I test to see if the two data sets are statistically different?
How to perform two t tests on a vector?
The t.test () function can be used to perform both one and two sample t-tests on vectors of data. The function contains a variety of arguments and is called as follows: t.test(x, y = NULL, alternative = c(“two.sided”, “less”, “greater”), mu = 0, paired = FALSE, var.equal = FALSE, conf.level = 0.95)
Can a t test be run between two datasets?
With a t-test you have only 2 alternatives: a) the two means are statistically different and b) the two means are not statistically different. It’s either a) or b). data are not normally distributed. As Rajiv wrote, if your DV is continuous data, you can run a t-test.
Can you test two samples of the same data?
You can test the data through two samples independent t-test or paired t-test depending upon the situation, if your response variable is quantitative continuous data. No. non-significant t-test does not mean that there’s no difference.