Result Analysis

Abstract

Introduction

I. INTRODUCTION AND BACKGROUND OF THE INDUSTRY OR USER BASED PROBLEM85

Student result analysis is a web based application developed for colleges to analyze the result and keep track of students.We are able to see the individual candidate’s results separately. Student result analysis system has been designed to carry out the mark analysis process in an educational institution.

The results of respective departments can be efficiently computed without much of manual involvement. Given the continuous rise in student population, tertiary institutions calculate examination result of students with the help of computer programs.

 Analysis of students information and their academic record is as important as examination result computation. The need for data use to inform decision-making in tertiary institutions cannot be overemphasized.

Over the years, many algorithms and programs to compute examination result of students have been developed. However, the use of programs that extends capabilities beyond examination result computation is not widespread.

The system provides a comprehensive solution to the demand of examination result computation as well as student information and academic record management. The system is resilient and written with the flexibility to accommodate future needs.

It is expected to encourage data use in tertiary institutions. Information from such data can facilitate decision-making and improve educational standards in tertiary institutions..

II. LITERATURE SURVEY FOR PROBLEM IDENTIFICATION AND SPECIFICATION

A. Literature Survey

Irjet Template sample paragraph .Define abbreviations and acronyms the first time they are used in the text, even after they have been defined in the abstract.

Abbreviations such as IEEE, SI, MKS, CGS, sc, dc, and rms do not have to be defined. Do not use abbreviations in the title or heads unless they are unavoidable

Quantitative studies of similar quality and methodology can be analyzed, compared, and aggregated using the tools of meta-analysis.  Calculators in systematic review manuscript development tools (e.g., RevMan) are often employed, but Excel templates can be used as well. 

The Centre for Cognitive Ageing and Cognitive Epidemiology at the University of Edinburgh (CCACE) adds that "a statistical synthesis should include numerical and graphical presentations of the data, and also look at the strength and consistency of the evidence, and investigate reasons for any inconsistencies.

"  More detailed information on meta-analytic summations or statistical synthesis can be found here.

III. PROPOSED DETAILED METHODOLOGY OF SOLVING THE IDENTIFIED PROBLEM WITH ACTION  PLAN

A. Steps to Start an Analyzing Data

1. Step One: Ask The Right Questions

Before you start collecting data, you need to first understand what you want to do with it. Take some time to think about a specific business problem you want to address or consider a hypothesis that could be solved with data. From there, you’ll create a set of measurable, clear, and concise questions that will help answer that.

For example, an advertiser who wants to boost their client’s sales may ask if customers are likely to purchase from them after seeing an ad. Or an HR director who wants to reduce turnover might want to know why their top employees are leaving their company.

Starting with a clear objective is an essential step in the data analysis process. By recognizing the business problem that you want to solve and setting well-defined goals, it’ll be way easier to decide on the data you need.Get the latest insights on data analysis delivered straight to your inbox

2. Step Two: Data Collection

This brings us to the next step: data collection. Now that you have a solid idea of your questions, it’s time to define what data you need to find those answers. As a starting point, you’ll want to determine if the data is readily available within your organization—like within employee survey results or annual performance reviews in the HR case.

Then, ask yourself: do you have all the data you need or will you also need to externally source it? If it’s the latter, you may decide to run an experiment or conduct another survey.

3. Step Three: Data Cleaning

You’ve collected and combined data from multiple sources. Great. But it’s not yet time to roll up your sleeves and dive into it. That’s because raw data is seldom usable in its current form. You’ll often find flaws within it, like missing values. While seemingly minor, these can actually be quite pernicious: even the tiniest inaccuracies can skew your results.

Here’s where you’ll spend some time polishing the data to ensure it’s in tip-top shape. This process, called data cleaning, consists of amending or removing incorrect or superfluous data, as well as checking for incompleteness or inconsistencies. For instance, you might clean spaces in front of letters or symbols or remove duplicates.

This is a vital step—because ultimately, the accuracy of your analysis will depend on the quality of your data.

4. Step Four: Analyzing The Data

You now have a wealth of data. You’ve spent time cleaning it up. It’s as organized as it’ll ever be. Now you’re ready for the fun stuff.

In this step, you’ll begin to slice and dice your data to extract meaningful insights from it. Using the techniques and methods of data analysis, you’ll look for hidden patterns and relationships, and find insights and predictions.

5. Step Five: Interpreting The Results

After you’ve interpreted the results and drawn meaningful insights from them, the next step is to create visualizations by selecting the most appropriate charts and graphs.

But pretty visualizations aren’t all that are needed here. If you want your valuable discoveries to be implemented, you need to be able to present it to decision-makers and stakeholders in a manner that’s compelling and easy to comprehend.

In this architecture, first of all admin login in the Result Analyasis. Then he will be redirected to Submit Subject, Teacher Registration Student Resistration. After Resistration it will be go to the set subject theory and practical and next give the marks of student as per subject .When user will enter this data. Then user can see the generated report of this data. .

IV. MODULE DESCRIPTION

1. Login
2. Registration

First of all the admin will be required to login using the username/email address and password which the admin has set. The login page is for security of the website ensuring that the website is accessed by anonymous person

References

[1] https://en.wikipedia.org/wiki/Student_information_s ystem [2] https://en.wikipedia.org/wiki/Systems_analysis

Copyright

Copyright © 2022 Miss. Sufiya Iqbal Tamboli , Miss. Pratiksha Vilas Tate , Miss. Shrinivas Prakash Kagwade , Miss. Harsh Tatyaso Magdum , Prof. Seema S. Chavan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.