**Literature Review & Research Problem**

In research, **statistics** is defined as a number that represents a property of a sample. It is important to understand statistics and apply it to a research in order to gain an understanding of data. In applying statistics, it should be started with a population or process to be studied.

**Population** is collection of all things/people/objects that are under study. This population data can be summarized by using **d****escriptive statistics**. As an example, there are 9 CDD students participates in Research Method class which consist of 5 females and 4 males. Descriptive statistics will help to organize and summarize that data into: F(5), M(4).

If the population data is over (e.g. 125.000.000 people to be census) and not feasible to be compiled, selected subject of population called a **sample** is studied. Sample data must be representative of the population to avoid **sampling bias **– some members of population are more likely to be chosen that other for the sample.

Sampling method is divided into two categories which are representative sampling (probability samples: random sample and stratified sample) and non-representative sampling (non-probability samples: quota sample, purposive sample, and convenience sample). In fact, the best sampling is representative sample because it reduces the possibility of subjectivity and bias.

**Inferential statistics** is needed to draw conclusions about the entire population through the sample data, accounting for randomness. The findings may based on: hypothesis testing, estimation, associations-correlations, or regression analysis.

Reference:

Research Methods. (2016). *Lecture 3: Intro to Statistics. *Sampoerna University

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