The **Data Analysis** is the process by which we can extract the useful information and all is happen when we pass our data through many steps, the steps are these:-

-Inspecting the data.

-Cleaning the data.

-Transforming the data.

-And last modeling the data.

These four are the key characteristics of the data analysis. The data analysis is used for the decision making. The Algebra data analysis is also a same approach that contains the same procedure to analyze the data. It is only used when we have algebraic data, equations and formulas. The aim of data analysis is same in all scenarios. Data analysis has many facets, methods, procedures, approaches and techniques so that we can easily analyze the data. The most common and useful technique for the data analysis is data mining.

Sometimes the data analysis can be considered as the data modeling. Before data analyzing, we should be familiar with the **types of data**, data can be following types: -

**Quantitative data**: - It means those types of data that can be measured in terms of number.

**Categorical data**: - It means variety of data.

**Qualitative data**: - It means that data that has good features.

Let’s see the step by step process of data analysis: -

Data cleaning: - This is the first useful step; in this step we examine the data, if errors are there then resolve them. The process of data cleaning is made at the time of data entry. During the data cleaning we need to maintain both the types of data that is updated data and original data. After it all the alterations should be properly documented.

Initial data analysis: - This analysis includes the following steps, that are:-

i) Quality of data:- In this phase we check the quality of data by doing the several operation on the data such as analysis of missing observations, frequency counts, mean - median, extreme observations analysis and many more.

ii) Quality of measurements:- After checking the data quality we determine the ways of quality measurements that are confirmatory factor analysis and internal consistency analysis.

iii) Initial Transformations:- In this step we do the transform for the one or more variables and for this we have some transformation such as Square root, long and inverse transformations.

**Main data analysis**:- This is the final step of data analysis that also includes the some steps:-

i) Exploratory and confirmatory approaches:- The exploratory approaches does not deals with the no clear hypothesis, it only find the data for the models. And in confirmatory approaches or analysis we only include the clear hypothesis.

ii) Stability of results:- In this we check that our results are reliable or not? To specify this we use two methods that are cross validation and sensitivity analysis.

Measure of Central Tendency Definition is a value that can describe a Set by its central data or in other words we can say that it describe a particular set of data by its central Position. Measure of Central Tendency has other name as well like measures of central and summary Statistics. Measure Of Central Tendency have three main parts, mean, mode and Medi...Read More

Matrices Mean arrangement of a group of elements in Square brackets. Mathematically a matrix ‘A’ can be written as [A_{ij}]_{m*n. }Here ‘I’ and ‘j’ shows the element Position in the matrix and ‘m’ is the number of rows and ‘n’ is the number of columns of the matrix. A matrix [A_{ij}]_{m*n }can be written in more simple way like

...Read More

Standard deviation z score is used to measure the deviation of data from its Mean. It is equals to Square root of variance or z score Standard Deviation tells us that how many data items are above and below the mean.

The formula is for standard deviation is:

S = √∑(x – x’^{2}) / N – 1

Where s = the standard deviation

X = ...Read More

A line which passes through the center of group of data points that are plotted on a scatter plot is known as line of best fit. Scatter plots are used to depict the results of gathering data on two variables and line of best fit is used to find whether these two variables are correlated or not. There are many methods for determining the line of best fit:

Line of best f...Read More

**A figure drawn using a number line to represent the distribution of data is known as box and whisker.** Along the number of lines a box and whisker plot is used to distribute a Set of data. The end value of the whisker denotes several possible alternative values among them.

The minimum and maximum value of data and Standard Deviation is used above and below the Mea...Read More