Skip to main content

Percentage to fraction Conversions

                                 Module - 1


The best practice,  while solving the problems on percentage is to calculate 50% , 10% and 1%.
Examples : 
1. For 500
Ans : For 50% is 
                    50/100 * 500 = 250 
          For 25% is
                    25/100 * 500 = 125
          For 10% is
                    10/100 * 500 = 50
          For 1% is 
                    1/100 * 500 = 5

Simple ways is  
  • For 50% , value is divide it by 2
  • For 25% , Value is divide it by 4
  • For 10% , Value is divide it by 10
  • 15 is divide it by 100


Examples : 
1. What is 49% of 500?
Ans : 
        We know for 50% we need to divide by 2 so 50% is 250, and for 1% is the value divide by 100 so 1% is 5.
        Then 49 = 50 - 1
                     = 250 - 5
                     = 245.

2. What is 32% of 200?
Ans : 
        We know for 10% we need to divide by 10 so 10% is 20, and for 1% is the value divide by 100 so 1% is 2.
        Then 49 = 10 * 3 - 1* 2
                     = 20 * 3 - 2 * 2
                     = 56.

3. What % is 25 from 200?
Ans :
            Then what is 25 part out of 200 in terms of percentage.
             25/200 * 100 = 12.5%

            Another Method :
                    100% = 200
                     ?% = 25
                    Then cross multiply = 100 * 25 / 200 = 2500 / 200 = 12.5%

4. What % is 50 from 200?
Ans :
            Then what is 50 part out of 200 in terms of percentage.
             50/200 * 100 = 25%

            Another Method :
                    100% = 200
                     ?% = 50
                    Then cross multiply = 100 * 50 / 200 = 2500 / 200 = 25%





Learn Data Science Material which helps to learn concepts in Python, Statistics , Data Visualization, Machine Learning , Deep Learning. And it contains Projects helps to understand the flow of building model , and what are the necessary steps should be taken depending on the data set. Interview Questions helps to crack the interview. 





Learn Python from basics to advanced. 



Join ML in python channel in telegram , Where you can learn every concepts in Python, Statistics, Data Visualization, Machine Learning, Deep Learning.

  

Join Aptitude Preparation channel in telegram , this channel helps to crack any interview.

Labels:

Comments

Post a Comment

Popular posts from this blog

Practice Problems in Python [ Part - 1 ]

                                            Python 1. Write a program which will find all such numbers which are divisible by 3 but are not a multiple of 7,between 2000 and 3200 (both included). soln :            def filter_numbers():           """           function to filter out numbers by extracting numbers           which is divisible by 3 but not multiple of 7.           """           filtered_list=[]           for i in range(2000, 3201):               if (i%3==0) and (i%7!=0):                   filtered_list.append(str(i))    ...
Post a Comment
Read more

Python Introduction

 Introduction  Python is developed by Guido Van Rossum and released in 1991. Python is high level, interpreted, general purpose programming language. It is one of the top five most used languages in the world. Currently there are 8.2 million developers who code in Python. Python is one of the most preferred languages in the field of Data Science and Artificial Intelligence. Key Features Python is an interpreted language, unlike compiled languages like Java, C, C++, C#, Go etc., Python codes are executed directly even before compiling.  Python is Dynamically typed, no need to mention type of variable before assigning. Python handles it without raising any error. Python codes can be executed on different software or operating systems without changing it. Python supports both Functional and Object oriented programming as it supports creating classes and objects. Python has high number of modules and frameworks support. Python is free and Open Source, which means it is availa...
Post a Comment
Read more

Types of Machine Learning

                                   Machine Learning  Machine Learning is an application of artificial intelligence where a computer/machine learns from the past experiences (input data) and makes future predictions. It finds the pattern in the data , based on the pattern it gives the future predictions from the unseen data.   It is a way to understand the data and find the patterns in that. Types of Machine Learning        Supervised Machine Learning An algorithm learns from example data and associated target responses that can consist of numeric values or string labels.  Generally the algorithm should find the pattern how input and output is mapped           Two types of Supervised Learning: Regression:  The problem is regression type when the output variable is real or continuous. Example :  Predicting salar...
Post a Comment
Read more