p-value

p-value (Hypothesis Testing) (GWU EMSE-271)
Index | Topics (Logical Lectures) | Lectures | Problems | Readings | References | Concepts [confidence intervals | null hypothesis | acceptance and rejection terminology | Type I and Type II errors | power | p-value]


 * "Definition: **The **p-value** of an hypothesis test is the largest significance level at which we fail to reject the null-hypothesis." - EMSE 271, Fall 2009 (Slide 75)

While introduced with the t-distribution, the P-Value is a concept that is applied with other distributions to (i.e. F-Distribution in regression) - Philip and Phillip

"The p-value is an indication of the support for the null hypothesis." If the p-value is ___A statistician would say the p-value is a measure against the null-hypothesis and would say fail to accept. - VanDorp, 9/16/2009.

Check - new slide 75 shows p-value in green. Need to download and insert graphic here. Not sure if he uploaded the corrected file for Fall 2009.

"In statistical hypothesis testing]], the **p-value** is the probability of obtaining a result **at least** as extreme as the one that was actually observed, assuming that the null hypothesis is true. The fact that p-values are based on this assumption is crucial to their correct interpretation.

"The //lower// the p-value, the //less// likely the result, assuming the null hypothesis, so the //more// "significant" the result, in the sense of statistical significance – one often uses p-values of 0.05 or 0.01, corresponding to a 5% chance or 1% of an outcome that extreme, given the null hypothesis." - [|Wikipedia]

"Threshold test" - Leslie

Contributors: Sisson, Schrader
 * Sources:**
 * EMSE 271, Fall 2009
 * P-value. (2009, September 11). In //Wikipedia, The Free Encyclopedia//. Retrieved 13:39, September 11, 2009, from []