The Dry Lab Stuff

When to use χ 2 test? χ 2 test is used to check the goodness of fit of data points calculated by a function against the observed data points. One of the applications I know of it is when unknown parameters when passed to a function give an observed data. function(parameters) --> data points In such cases we can back calculate the parameters from observed data points. The way to solve these problems is to optimize the parameters by passing them to the functions and trying to minimize the sum of squared differences (SSR) of the calculated and observed values. Following is a rough pseudo-code for this.

ANOVA (Analysis of variance) is an statistical methods used when we want to see if some treatment or strategy has produced any significant effect on the outcome or not. One-way ANOVA is used when only one factor is being tested. Two-way ANOVA is used when two factors are being tested at once. For the ANOVA, something called as a F-value is calculated by the following formula: F v a l u e = S S B S S W where, SSB = sum of squares between groups SSW = sum of squares within groups Also, based on the degrees of freedom within and between the groups, a F-critical value and a P-value is obtained. If the calculated F-value is greater than the F-critical value it is inferred that the treatment of strategy has statistically significant effect on the outcome. The P value is the probability of F-values to be greater than or equal to the calculated F-value if there was no effect o...