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Quantitative Data Analysis

In simple terms, quantitative data analysis just refers to giving meaning to the collected raw numerical data.

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Know More About Quantitative Data Analysis

Using rational and critical thinking, the data collected through close-ended questionnaires is analysed to take a meaningful shape. The quantitative data analysis includes calculating the variable frequencies, evaluating the differences or correlation between various variables and other tasks like building statistical models. The analysis process is used to come to conclusions that either support or reject the set research hypothesis.

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Common Statistical Softwares Used For Quantitative Analysis

Here are some of the pros and cons of these most popular statistical tools:
Pros of Microsoft Excel

This tool is considered to be highly cost effective as it is free of cost. It can be sent or shared via email and other apps easily as it is mobile friendly as well. Moreover, to ensure the protection of data, the excel sheets also come with the lock/password protection as well. It provides an all-in-one program too.

Cons of Microsoft Excel

Microsoft Excel does not provide a smooth working experience on a large number of files as the number of rows and columns have limits. It also works slowly on heavy files. For the beginners, learning the advanced tools on excel can get tricky and time consuming. With these issues, there is also a risk of viruses entering the files through macros.

Pros of SPSS

The SPSS software comes with a wide range of formulas and statistical routines which can be used for complex calculations as well. There is no issue in importing files from other programs to SPSS as well. Moreover, the yearly update keeps increasing the proficiency of the result.

Cons of SPSS

Due to the advanced techniques, SPSS becomes a costly software. There is a limit of license and thus, it needs to be renewed time and again. Other than this the constant updates and changes in version makes it harder to understand all it tools and leads to confusion oftentimes.

Process Of Quantitative Data Analysis

For a successful analysis, the process needs to be divided into stages needs to be followed in an orderly manner.
1. Stage 1

The first stage consists of preparing the data and running the reliability test to check whether the data is suitable to be used for fulfilling the research objectives.

2. Stage 2

The second stage includes the data input process and choosing whether it will be more suitable to put it into tables, charts or diagrams.

3. Stage 3

In the third stage, it is important to select the suitable statistical measure that describes your data.

4. Stage 4

Lastly, the fourth stage includes examination, evaluation and analysis of the data using the chosen technique.

Methods Of Quantitative Data Analysis

Based on the research objectives and on the size of data that needs to be analysed, there are two major categories of data analysis namely; descriptive statistics and inferential statistics. In case of simple statistical analysis, descriptive statistics is used to describe the population through tables, graphs and charts. Whereas, inferential statistics is used when there are more than one variable affecting the prediction about large data.

Descriptive statistics involves calculating mean, median, mode, frequency, range or percentage of a simple data collection. However, it is important to decide which of these measures is best with the set research hypothesis. On the other hand, inferential statistics includes the evaluation of correlation, regression and variation analysis. Due to this, it is also known as a bivariate or multivariate analysis.

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Why Choose Services From PhD Thesis Help?

In-Depth Software Knowledge

Our expert team of statisticians in Mumbai, Pune, Nashik, Aurangabad, Nagpur are well-equipped with the latest versions of the software which allows us to provide you with the precise conduct of the analysis process. This in-depth knowledge is used to comply effectively with the steps of data management, evaluating research objectives, conducting tests and developing results.

Provide Data Check

Before starting with the analysis process, we check the data for its reliability and accuracy. It helps in making sure that the data collected is accurate and saves a lot of time instead of realising it after analysis that the data is not suitable for the set hypothesis.

Other Related Services

In case you need other related services like developing questionnaires, collecting data or interpreting data for creating reports, our team in Mahrashtra can help you with that as well. We can provide you chapter by chapter services and updates as well so that you can give your inputs side by side without consuming more time than it is required.

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Starting with Research

  • Topic Selection
  • Problem Identification
  • Proposal Preparation
  • Literature Review
  • Review Paper

Software Implementation

  • Matlab
  • NS2
  • Java
  • Python

Conducting Research

  • Questionnaire Designing
  • Implementation Plan
  • Data Collection
  • Empirical Paper Development
  • Technical Paper Development
  • Data Analysis

Finishing with Research

  • Chapters Writing
  • Editing Journal Publications

Data Analysis

  • Quantitative Data Analysis
  • Quantitative Data Analysis

Free Services

  • Plagiarism Checking
  • Initial Research Discussion
  • Formatting of PhD Thesis
  • Peer Review Manuscript
  • Thesis Writing Software

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