Histogram of unequal class width

In summary, the conversation discusses the concept of frequency in relation to class size and the resulting bar graph. It is important to consider the area of the bar in the graph, which may change if the data is binned differently or normalized to a different class width.
  • #1
kelvin macks
60
0
for the class 100-199, the f (number of household) is 20, but in the histogram, the frequency is divided by 2 which 20/2 = 10 , but how can it show that in the class 100-199 , the total frequency of 100-199 is 10 ? when i look at the histogram, i would directly think that there are f=10 in the class of 100-199... how can it relate to the f for 100-199 is 20? i totally can't undrestand.
 

Attachments

  • IMG_20140616_064107[1].jpg
    IMG_20140616_064107[1].jpg
    34.2 KB · Views: 1,473
  • IMG_20140616_064133[1].jpg
    IMG_20140616_064133[1].jpg
    34 KB · Views: 663
Physics news on Phys.org
  • #2
Imagine that you had ##f=10## for class 100-149 and ##f=10## for class 150-199, what would the bar graph look like? Now imagine that the some of the information is lost, and you only know that ##f=20## for class 100-199. Why should the graph then be different? (Note that I split it into two times 10 for illustration purposes. In reality, this is only true on average. Increasing the class size means that the average is taken over a greater interval.)

What is important is the area of the bar in the graph.
 
  • Like
Likes 1 person
  • #3
DrClaude said:
Imagine that you had ##f=10## for class 100-149 and ##f=10## for class 150-199, what would the bar graph look like? Now imagine that the some of the information is lost, and you only know that ##f=20## for class 100-199. Why should the graph then be different? (Note that I split it into two times 10 for illustration purposes. In reality, this is only true on average. Increasing the class size means that the average is taken over a greater interval.)

What is important is the area of the bar in the graph.

i can understand your explanation. why can't i just draw f=20 for 100-199? since the question only give f=20 for 100-199
 
  • #4
shall i label the y-axis of the graph above as frequency density?
 
  • #5
kelvin macks said:
i can understand your explanation. why can't i just draw f=20 for 100-199? since the question only give f=20 for 100-199

Because you have to normalize the data to take into account the class width. The total area must be the same whatever you choose as the size of the bins.

Say there is no household that consumed less than 100 kWh. You could then make the class go from 0 to 199, and you would still have ##f = 20##. Do you still think that the bar should go up to 20 from 0 to 199?
 
  • #6
kelvin macks said:
shall i label the y-axis of the graph above as frequency density?

I'm not sure if it's appropriate to call it that. I'll leave it to others to answer that.

It is true that the y scaling would change if the original data had been binned in smaller bins. Here, the data is normalized to what they call the "standard width."
 

What is a histogram of unequal class width?

A histogram of unequal class width is a type of graph that represents the distribution of numerical data. It is similar to a regular histogram, but instead of having equal class intervals, it has intervals of varying sizes.

Why would you use a histogram of unequal class width?

A histogram of unequal class width is useful when the data being represented has a wide range of values. It allows for a more accurate representation of the data by grouping similar values together.

How is a histogram of unequal class width created?

To create a histogram of unequal class width, you first need to determine the range of values in the data. Then, divide the range into intervals of varying sizes. Finally, count the number of data points that fall within each interval and plot them on the graph.

What are the advantages of using a histogram of unequal class width?

One advantage of using a histogram of unequal class width is that it can better capture the shape of the data distribution. It can also provide more detailed information about the data, such as the frequency of values within each interval.

What are the limitations of a histogram of unequal class width?

A histogram of unequal class width can be more difficult to interpret compared to a regular histogram with equal class intervals. It also requires careful selection of interval sizes, as too few or too many intervals can distort the data.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
991
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
  • High Energy, Nuclear, Particle Physics
Replies
9
Views
2K
  • Engineering and Comp Sci Homework Help
Replies
2
Views
4K
  • Introductory Physics Homework Help
Replies
16
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
1K
  • Linear and Abstract Algebra
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
5K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
784
Back
Top