Introduction

Population & Sample

1. Population indicates the whole or entire group of data information that is to be analyzed.
2. Sample indicates specific group of data from which you collect.

As it is difficult to gather data from the whole population, we normally randomly collect data from sample and infer the population using sample data. Therefore, sample is always less than population.

Hypotheses

Hypothesis in statistics indicates the method used to determine if there is enough evidence in a sample data to draw conclusions about a population. Building appropriate hypothesis is critical in terms of

1. choosing the appropriate research framework,
2. allowing researchers to formulate testable predictions,
3. designing studies effectively,
4. and draw meaningful conclusions about populations based on sample data.

Null Hypothesis

Null hypothesis (which is often noted as $H_0$) indicates hypothesis that there is no difference between groups or no relationship between variables. In other words, null hypothesis is the statement that

Alternative Hypothesis

Alternative hypothesis (which is often noted as $H_1$) refers to statement that is being tested against the null hypothesis. In other words, alternative hypothesis is the statement that

Measuring Variables

When it comes to measuring variables, data can come into two different forms: 1. Categorical (Qualitative) variable and 2. Continuous (Quantitative) variable.

1. Categorical data: Data that is measured in numbers (e.g. heights, weights)
2. Continuous (Quantitative) data: Data for placing “things” into different groups or categories (e.g. hair color, type of cat)