# Data Analysis Techniques

Oct 21 • General • 10659 Views • No Comments on Data Analysis Techniques

Millions of people are living in this universe. Everyone wants to know about the happening facts of this world, How this world works ? From where the resources came and where it goes ?  All the answers are hidden behind the data. After a complete statistics of data, we may able answer all the questions. Data Analysis will give you the idea after analysis of different data. Data Analysis will help us to know about all the facts and the different hypothesis. In this section, you will able to learn the different methodologies , types of data Analysis and more about the data analysis.

Analyzing the data is an important part in the research method. There are several steps that are included in data analysis.  These steps are as follows :

• Error checking and verification– this stage involves different steps like editing, coding, and keyboarding
• Data Analysis, this can be done through different methods like descriptive analysis, univariate analysis, bivariate analysis, multivariate analysis
• The data obtained after analysis is then interpreted into useful information.

Types of Data Analysis

What is Data Analysis ?

• Data processing – General
• Statistical analysis – Specialized (Univariate, Bivariate, and Multivariate)
• Data Processing – this application is for coding and entering data for all respondents, for all questions on a questionnaire.
• Data Input Format – The input follows a matrix format, where the variable appears on the column heading, and data for one person is entered in one row.

Editing

It is the process in which the data is ready for the purpose of coding and is transferred to the data storage, this is known as editing. Its purpose is to ensure the completeness, consistency and reliability of data.

Types of editing:

• Field Editing – preliminary editing by a field supervisor on the same day as the interview; its purpose is to catch technical omissions, check legibility of handwriting, and clarify responses that are logically or conceptually inconsistent.
• In-house Editing – A rigorous editing job performed by centralized office staff.

Coding

The process of identifying and classifying each answer with a numerical score or other character symbol is called coding.

• Code – A rule used for interpreting, classifying, and recording data in the coding processes; the numerical or other symbol assigned to raw data.
• Field – A collection of characters that represents a single type of data.
• Record – A collection of related fields.File – A collection of related records.
• Data Matrix – A rectangular arrangement of data into rows and columns.

What is Analysis?

Analysis of data is the process by which data is converted into useful information.

Types of Analysis:

• Univariate, involving a single variable at a time,
• Bivariate, involving two variables at a time, and
• Multivariate, involving three or more variables simultaneously.

Simple and cross tabulation

• Dependent and Independent Variables – two variables are called independent variables if a change in one does not influence or cause a change in the other. But if a change in one variable causes a change in the other, the first one is called an independent variable, and the second one is called a dependent variable.
• Demographic Variables – variables such as age, location, income, occupation, sex, education are generally independent variables for the purposes of marketing studies, because other variables depend on them.

Data Model