Lorenz Curve Assignment & Homework Help Online
HelpwithAssignment.com is the best place that caters to all your queries regarding statistics and Lorenz curve assignments of students and provides high-quality solutions. We provide original and plagiarism-free assignment solutions at reasonable rates and that’s what makes us highly recommended by students worldwide.
Lorenz Curve is a probability distribution curve that is used for measuring the variability of a statistical series. This curve was developed by Max Lorenz in 1905. The curve is very popular in Economics for measuring the distribution of wealth and income in society.
Lorenz Curve measures the standard deviation of an actual distribution from the line of equal distribution. Put it simply, it measures the deviation of a present distribution from an imaginary or hypothetical distribution.
The difference between the actual distribution and the hypothetical distribution or the extent of deviation is known as Lorenz Coefficient. The greater the difference or deviation of the Lorenz Coefficient, the greater is the inequality or variability in the distribution. In the same way, if the difference is lower in comparison then it can be said that the inequality or variability in the distribution is lower.
Constructing a Lorenz Curve
Here are the steps for the construction of Lorenz Curve
- A discrete series is taken and the values are converted into cumulative frequency series. Assume that the cumulative sum of items is 100 and the items in the cumulative sum are converted into percentages of the sum of frequencies.
- On X-axis, these cumulative frequencies are plotted and on Y-axis the cumulative items are plotted.
- Take a graph sheet and mark both X and Y axes taking values from 0-100.
- Now, draw a line diagonally from X (0,0) to Y (100, 100). This is the equal distribution line or the Line of equal distribution.
- Now, in the graph sheet, mark the cumulative frequency values and compare them with the Line of equal distribution.
- You can take the highest point of difference between the line of equal distribution to the line of actual distribution.
- This line of Actual Distribution is called the Lorenz Curve, where the greater the difference, the larger the gap, and vice versa.
Application of Lorenz Curve
Lorenz Curve is applied in a number of studies or subjects. One of the subjects where the Lorenz Curve has been applied more is in economics. In economics, Lorenz Curve is used for studying income distribution, wealth distribution, wage distribution, profit distribution, production distribution, population distribution, etc.
Image Credit: Wikipedia
At Help With Assignment, our Statistics tutors and Economics tutors offer a good explanation of the Lorenz Curve and its applications in different areas. Our Statistics assignment help and Statistics homework help cover all of the probability distribution curves in Statistics and Lorenz Curve is one of them. Lorenz Curve is taught by our tutors who’d explain the concept behind Lorenz Curve, the need for preparing Lorenz Curve, the method for preparing Lorenz Curve, etc along with its advantages and disadvantages as well.
Background of our Lorenz curve assignment experts
- Our expert holds Ph.D. in Statistics and has conducted numerous seminars. He also published many research papers in statistical journals. He has a strong hold on the subject and his years of experience will definitely help students to solve their assignments easily.
- Our next expert holds a Master’s degree in statistics and currently pursuing Ph.D. from a reputed university in the US. She has extensive knowledge of the subject and solves a multitude of problems on daily basis through online conversation.
Feedback on our Lorenz curve assignment helps students
- “Dissertation paper completed on time and this credit completely goes to HelpwithAssignment.com. Thank you so many guys, it’s only just because of you that I completed on time and got a good job”. -Austin, July 2016
- “My main concern was the relevant research and reference work that is required in my Masters’s course at the university. They are very particular about referenced and researched assignments. With the stats experts at HelpwithAssignment.com, I have never had to worry about that since the experts provide the most excellent and relevant references in all my assignments which help me get top marks in the class”. Amanda Swift, Sep 2016
Advantages of HelpwithAssignment.com
- Unique and Plagiarism free
We use plagiarism detection software like Turnitin to ensure that writing services are un-referenced and taken from publicly available resources. We always provide 100% original papers.
- 24/7 customer support helpdesk
If you have any queries regarding the subject, you can approach our customer support executives 24×7 via phone, email, or live chat.
- On-time delivery
Our writers make sure that your assignment is completed prior to your deadline so that you can proofread your paper before submission.
- Ph.D. qualified and experienced subject experts
Knowledge, experience, and creativity are the three important aspects we consider before hiring a writer. All our writers are Ph.D. degree holders from reputed Universities around the world. It will be a great learning experience and a privilege to get assistance from these experts.
- Cash back guarantee if not satisfied
Your payment is secured and a 100% refund is guaranteed, if you are not satisfied with the services.
Get Lorenz Curve assignment help here
Fill up the assignment help request form on the right or drop us an email at support@helpwithassignment.com. Feel free to contact our customer support on the company 24/7 Live chat or call us at 312-224- 1615.
HelpwithAssignment.com provides timely help at affordable charges with detailed answers to your assignments, homework, research paper writing, research critique, case studies, or term papers so that you get to understand your assignments better apart from having the answers. The team has helped a number of students pursue education through regular and online universities, institutes, or online Programs.
