# Basic Statistics Information Series

First of all, Hi, I am Taner. I am student at Ege University Statistics Department. I wanted to spread the knowledge by sharing with you like what I learned from my course and what I continue to learn from my department. Statistics is the science of collecting data for a specific purpose, summarizing with tables and graphs, interpreting results, sampling confidence levels of results, generalizing the result obtained from the samples to the audience, making predictions for various applications, making predictions for various future, experimentation and observation principles.

Areas of Application:

• Economy + Statistics = Econometrics
• Psychology + Statistics = Psychometry
• Medicine + Statistics = Biostatistics
• Sociology + Statistics = Sociometry

Statistics have much area of working with statistics knowledge. It concerned with data. Data is the oil of the 21st century. Statistics have relationship between life. Actually, statistics are everywhere because when you walk around and it comes street so you have to choose one of them. There is a statistics in there. Even if you do not realize it, you will be using the issue of probability in statistics, when choosing a path for walking.

## Statistical Definitions

Mass = It is a set of measurements obtained from units or objects with a certain property. The number of units in the mass is denoted by “N”.

Sample = It is a subset that is thought to represent the population withdrawn from the bag and consists of fewer individuals or observations than the population.

Sample Size = The number of observation or individuals in the sample. It is denoted by “n”. The sampling size process includes several specific activities, namely:

• defining the mass that is the target of the research
• choosing the sample size scale
• building the modalities of the selection of the sample size units
• determining the main of the sample size
• choosing the real units of the sample size

I can say for sample size activities.

Descriptive Statistics = Descriptive statistics are brief descriptive coefficients that summarize a given data set, which can be either representation of the entire or sample of population. Descriptive statistics are broken down into measures of central tendency and mesaures of variability.

Inferential Statistics = It takes the possibility and draws conclusion about a larger statistical stack. These results can be yes/no answers, as well as in the form of estimating numerical properties, predicting future values, interpreting or modeling the relationship / relationships between data.

Randomness – Uncertainty = Randomness means that no information is used when choosing a sample from a population. For example, if we choose a top from the bag with balls of the same size and different colorsa inside, without looking inside the bag, this selection process will be random. The coice we get by looking inside the bag will not be random. If the outcome of an event is uncertain, that event is a random event. It deals with the outcomes and results of the experiments in many problems in statistics.

This article is over here. I will continue to present this article series as a series in the coming days. Have a good day.

## Benzetimli Tavlama (Simulated Annealing) Algoritması

BENZETİMLİ TAVLAMA ALGORİTMASI Herkese merhabalar, optimize kelimesi aslında günlük hayatta...

## Python Data Science Libraries 2 – Numpy Methodology

One of the most important and fundamental libraries in Python...

## Python Veri Bilimi Kütüphaneleri 2 – Numpy Metodoloji

Python içerisinde en önemli ve temel olarak bakılan kütüphanelerden birisi...

## Psychiatric Illness and Social Media

Is there any psychiatric illness of yours based on your...