Type I & Type II Error, p-value, Null Hypothesis,Community Medicine tutorial,NEET PG 2020, fmge.

In this video I shall discuss about types of estimation, hypothesis testing, STATISTICAL errors TYPE I and TYPE II, p value. Estimation is the process of estimating an unknown population parameter from a known sample statistic. Hyptothesis is an assumption that needs to be verified. Hypothesis testing is the process that helps us decide whether population parameter is same as the sample statistic or there is a difference between population parameter and sample statistic. Null hypothesis does not show any treatment or association effect and alternate hypothesis shows an association or treatment effect.
Statistical errors are of two types. Type I error is when the null hypothesis is true but it is rejected. Type II error is null hypothesis if false but accepted. Type I error is more serious.
How much of an error that can be allowed is denoted by propbablity or p. Probablity denotes how much of a statistical error we can allow or denotes the evidence against rejecting a null hypothesis.
By convention it has been set as 5% or level of significance is 5%.