Statistical Inference

• Statistical inference refers to the use of information obtained from a sample in order to make decisions about unknown quantities in the population of interest.
• Since all population may be characterized or fully described by their parameters, it is important to make inferences on the one or more parameters whose values are unknown
• There are two main types of inferences
1. The hypothesis testing branch involves making decisions concerning the value of a parameter by testing a per-conceived hypothesis.
2. The estimation branch involves estimating or predicting the unknown value of a parameter.
• Both approaches involves the use of sample information in the form of sample statistic corresponding to the population parameter in question.
• Both approaches also rely on the "goodness" of the inference, which requires complete knowledge of the sampling distribution.