Hypothesis Testing
Hypothesis testing is the analysis of data using statistical methods, to assess if a statement (hypothesis) is true. Typically you form two possibilities: a Null Hypothesis proposing that there is NO statistical significance in the given set of observations, and an Alternative Hypothesis that contradicts the Null Hypothesis. The Alternative Hypothesis is what you are trying to test. If the finding is statistically significant, you reject the Null Hypothesis. Suppose you want to find out if a group of 11-year old children has the same average weight as the population's 11-year old children (problem). You would state the Null Hypothesis and the Alternative Hypothesis as: `H_0: bar x = mu` `H_1: bar x != mu` where `bar x` is the sample group mean weight of 11-year old children `mu` is the population mean weight of 11-year old children Pictorially you are trying to prove this. Two-Tailed and One-Tailed The above scenario is called a Two-Tailed test, as we are proving equality. A One-T