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What are dependent and independent variables?
The terms "dependent variable" and "independent variable" are used to distinguish between two types of quantities being considered, separating them into those available at the start of a process and those being created by it, where the latter (dependent variables) are dependent on the former (independent variables)
What is a Null Hypothesis
- The practice of science involves formulating and testing hypotheses, assertions that are capable of being proven false using a test of observed data. The null hypothesis typically corresponds to a general or default position. For example, the null hypothesis might be that there is no relationship between two
- measured phenomena or that a potential treatment has no effect.
It is typically paired with a second hypothesis, the alternative hypothesis, which asserts a particular relationship between the phenomena.
- The null hypothesis can never be proven. A set of data can only reject a null hypothesis or fail to reject it.
- For example, if comparison of two groups (e.g.: treatment, no treatment) reveals no statistically significant difference between the two, it does not mean that there is no difference in reality. It only means that there is not enough evidence to reject the null hypothesis (in other words, one fails to reject the null hypothesis).
What is a Standard t-test?
The most basic type of statistical test, for use when you are comparing the means from exactly TWO Groups, such as the Control Group versus the Experimental Group.
E.g: When testing a cognitive enhancing drug. There may be a control group (taking a placebo) and an experimental group (taking the active drug). Both groups may undergo neuropsychological assessment before and after taking the meds. The average score for each of the two groups would then be calculated and a t-test would be run to see if a “statistically significant” difference in their performance can be detected . The t-test returns a p-value that expresses the probability that the null hypothesis is wrong
What is a Paired t-test?
An extremely powerful test for detecting differences. It is usually used for “Before vs. After” type experiments, where the same individuals are measured before and after the application of some sort of treatment. It can also be used for “Left vs. Right” experiments, where two sides of an individual are given two different treatments.
What is a OneWay ANOVA?
Similar to a t-test, except that this test can be used to compare the means from THREE OR MORE groups (ttests can only compare TWO groups at a time, and for statistical reasons it is generally considered “illegal” to use ttests over and over again on different groups from a single experiment).
What is a TwoWay ANOVA?
A very useful statistical test, because it allows the comparison of the means of TWO OR MORE groups in response to TWO DIFFERENT INDEPENDENT VARIABLES. With this test available, an experiment can be set-up in which each member of the sample is exposed to a varying level of two different treatments. This test allows the comparison of a mean Response Variable relative to two different conditions.
What is Linear Regression?
One of the most common and useful statistical tests. This is for comparing the means of Groups along a continuum of THREE OR MORE treatment levels, such as a gradually increasing depth of water. It can also be used to compare response means under THREE OR MORE treatments set at regular intervals. It can also be used for a sequence of treatments at irregular intervals. One of the products of a Linear Regression is a graph with a perfect “Best Fit” Line that passes as close as possible (“closest to the mostest”) to all the data points.
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