Likelihood Ratio Test is used in statistics to see how well one model fits the other. One model is referred to as the null model and the other is called the alternate model. A likelihood ratio is a ratio which tells how likely is the set of data to be under one model than the other. Based on this one can reject or accept the null model in favor of the alternate model. The likelihood ratio is used to compute the p value.
The p value is the probability of obtaining the test statistic to the extent of as extreme as the one that actually occurred. The ratio could also be compared to critical value, that is the cut off or significant value.
Generally two types of errors can occur while doing so. Type one error occurs when you reject a null hypothesis when it is true. Type two error occurs when you accept a null hypothesis when it is false.