Friday, 13 January 2017

Sample and Population

Population: let's say you want to see how many people in your city like potatoes.  In statistics,the collection of all the people about whom you are going to draw inferences is called population.  In this case, it is the total number of people in your city.

Sample: a sample can be defined as the subset of the representative population from which the data is collected.  In order to be effective and to be truly representative of the population, the sample has to be random. In this case, it will be a group of people randomly selected from the population.


Let's say we are testing the effects of a drug on cancer patients.

Hypothesis - is an idea that is based on solid facts but is yet to be tested. Based on facts, the hypothesis predicts the outcome. But the outcome has not yet been tested.

Hypothesis Testing - is a step by step procedure that helps us decide whether or not the results of a research based on a sample supports a hypothesis when applied to a population. Lets say the drug is tested on 3 patients and it works in 2. What is the inference? Does this mean it would work on 2/3 of the population? A hypothesis testing will help you decide.

Null hypothesis - assumes that the hypothesis to be tested has no effect on the outcome of the research experiment - assumes that the drug has no effect on cancer patients.