# Introduction to Statistics

Introduction to Statistics is a wide range of subject. In the different field, they are using statistics with the applications. referred that the statistics are a method. To analyzing, collecting, interpreting and drawing conclusions from the information. In another method, the scientists and mathematicians say that. Introduction to Statistics developed for collecting the data from interpreting and drawing conclusions. Everywhere it deals the collecting and processing and interpreting the data. The presentation also depending on the domain of the statics. Those activities are also done by the only statistics. ## Methods of Statistics

The Methods of Statistics can be classified into two types in data science. They are

· Descriptive Statistics

· Inferential Statistics

### Descriptive Statistics

It explains basic features of the study. They offered a simple review of the samples and measures. Simple graphics analysis used to form the basis of real quality analysis of the data. The descriptive statistics in Introduction to Statistics can break down. Into the measures of central tendency, measures of variability. And the smallest and largest variables. The measures of central tendency include the mean, median, and mode. The measure of variability includes the standard deviation and variance.

### Inferential statistics

Here inferential statics may be used to study or assume the sample data. That might be population think. And this may use to judgment in the probability. The group’s difference might be different in the one or more changes in the study.

#### Statistics:

it has some rules, regulations, concepts, and procedures. They used to

- Organize: The numerical information must be in form of tables, graphs, and charts.

- Understand These statistical techniques used to take decisions in our lives and well-being.

- Make: Those are making informed decisions.

#### Data:

The data collected by the observations. Facts and information. That comes from investigations.

· Measurement Data: Sometimes the quantitative data known as measurement data. Some instruments used to collect the data(ex. Weight, test score)

· Categories data: It is also known as the qualitative data or frequency. According to this some properties or things grouped. And the number of members are also recorded (vehicles, males/females etc.)

#### Variable:

In the variable system the objectives. Or events can take as properties in different values.

· Discrete Variables: The variable has a limited number of values.

· Continuous variables: In this variable can take any value in many different values. Between the highest and lowest points on the measurement scale.

· Independent Variables: This variable can be taken as the measured. Selected or manipulated by the researcher. It was taken by the observed behavior on the antecedent condition. The hypothesized cause-and-effect relationship may depend on the cause of the different variable. It affects the outcome.

· Dependent variable: The variable dependent on the independent variable. That may observed or measured in the response of the independent variable.

· Qualitative Variable: This variable based on the categorical data.

· Quantitative Variables: This variable based on the Quantitative data.