In this video, we will learn about frequency distributions, and once we know about frequency distribution,
we will learn how to draw a histogram.
So when we are trying to draw frequency distribution, we are basically trying to summarize the data
so that we have different categories from that data and we assign the number of occurrences of each
category in that data.
For example, if I have laid off students of a college and against their name, I have the branch that
they belong to, I can create a table like this in which I have summarized that how many of those students
belong to each branch?
So in an engineering college in that list, 100 students belong to a computer science branch.
It is to belong to mechanical engineering branch and so on.
When we have the categories like this, that is the categories are discrete.
We have five different branches and to each branch we can clearly assign the student.
This is called qualitative data or categorical data.
And this type of distribution is called a frequency distribution for qualitative qualitatively.
So the raw data would be student name in front of that is right on the branch to which that student
belongs.
And we have this list for 420 students and we summarize the data as how many students belong to each
group.
Once we have a say in these frequencies, we can also find out the relative frequency of each category
by using this formula that is frequency of that category divided by sum of all frequencies.
That is, if I want to find out the relative frequency of students belonging to biotechnology.
It is 60.
That is the frequency of this category divided by the total frequency, which is four.
Twenty is equal to nearly fourteen point two percent.
So when we build a frequency distribution for qualitative data, that is there are clear, discrete
categories and we draw a graph of it.
It is similar to a budget.
A graphical representation of frequency distribution for qualitative data is known as budget budget.
We have already discussed we know how to draw a budget.
If we have a data like this, you can just select the data in exile and go to budget and draw this kind
of graph.
The next type of frequency distribution is frequency distribution for quantitative data.
That is continuous data.
So for example, if I have a of student and in front of them I have the marks of these student inScience.
So Marks is a continuous value from zero to 100.
If I want to straightaway create categories, maybe I'll get one hundred category one category of zero
one category of two, one category of value tree.
And that does not really make a sense.
So when we have a continuous data, we try to create ranges, small ranges, and within each range we
assign the frequency of number of instances belonging to that category to, for example, instead of
creating zero one, two, three as categories, we have greater data 235 as one category 35 to 55 is
another fifty five to seven days another and so on.
And within each range I have found out how many students belong to that range and assign that number
here to this table is frequency distribution for a continuous data.
And when we create a graph of this data that is called a histogram, so a graph of frequency distribution
of categorical variable is called Barcia.
A graph of frequency distribution of continuous data is called a histogram.
So how to draw a histogram when you have continuous data?
I have outlined that process in these steps.
When you have a list of continuous data, the first thing you need to decide is the number of classes
that you want.
That is the number of categories.
For example, in the previous example, we have five classes.
So first thing you need to decide is how many classes you want in your table.
Second, using that number of classes, we find out the class without using this formula, the maximum
value of data and the minimum value data.
What is the difference between these two values divided by the number?
After that, we decided in was that once we have class that we can start creating the classes, we start
by the minimum value, we add classwork and we get the first class.
This will get clear when we go through the example.
This is the continuous data that I have.
It's a set of 20 numbers and I want to segregate into five equal classes.
So I have selected a number of classes, which is five.
Now I want to point out the class which I told you class with this one by subtracting minimum value
from the maximum value, minimum value for this set of numbers is six and the maximum value is 36 to
36 minus six, divided by number of classes, which is five.
So it comes out to six now to create the classes.
I will start with the minimum value, which is six, and I will add the class glasswork to get this
upper range.
So is six to 12.
Next class will start from this value will and we will add the glasswork to get it in and so on.
So from six to 12, 12 to 18, 18 to 24, 24, 30, 32, 36.
To avoid confusion, that if we have a number 30 to which class it will belong, we usually follow this
convention that 30 will not belong to this class, it will belong to this 24 to 30 class.
That is, that they will be part of the upper range and not of the lower range.
Once we have created these classes, we have to start assigning each number to these classes.
So I will go to the numbers one by one and I'll start adding a mark to each of the classes to whichever
class that number belongs to.
For example, I start with 10 and belong to this class.
So at the market then there is 14, for they belong to this class.
I am a mark here.
I go through all these numbers and I continue adding marks.
In the end, I have this column containing tally which is giving me how many numbers belong to each
category.
Lastly, I just need to add these marks to get the frequency.
So this is how this table is created and what this table is created.
We can create the histogram, so let us go to Excel and create this histogram.
So here is the list of numbers that I had in my presentation.
And this is the histogram which is created for these numbers.
The good thing about Excel is that you do not need to create that table to create this histogram.
Excel can create this histogram straight away using these numbers.
You can see from six to 12, we have two from 12 to 18, we have four.
So basically the classes are on the horizontal axis and the height of the bar is giving you the frequency
in each class.
One small but important thing to note here is that Excel is using this code and square brackets to indicate
that which number is included and which is not, for example, in this 24 to 30, 24 number will not
be included in this graph.
Therefore, it has a record, but 30 will be included in this, but therefore it is a square bracket.
So you can see for these four categories, the first number is not included, but this second is included.
But for this first category, only the first and second board are included.
This is our histogram will look like.
Let us learn how to create this histogram and delete this first to create a histogram.
Select the numbers that we have got to insert in these statistical graphs.
This first option is a histogram you can see by default.
It has created three classes with the range six to sixteen, 16 to 26 and 26 to 36.
Now I wanted five classes, so for that I will do the format access to opening for my lectures.
You know how to open this formatting options either.
Right, click and select the format option or you double click on that element to open formatting options
for that particular element.
So I double clicked on the horizontal axis to open it formatting options in these.
The third option will have the specific exit options for histograms.
Here you can change the bandwidth and number of bins by default automatically created three.
Now I want to create five and now either I give a benefit of value six, which I found.
OK,
so this is the histogram that I wanted to see.
Or I could have given the number of bent as you to both will work.
Also, remember, whenever you draw histogram, it is advisable that you have data labeled on top of
it.
It'll make it easier to find out what is the frequency of each category.
The second type of statistical chart is a burrito chart, so this is a burrito chart.
It is similar to the histogram.
The major difference is the categories are separate, these are sharper in the sense that the category
which is contributing the most comes first to this category had a frequency of nine to it is coming
first next county category, which is contributing the next maximum to the total.
So the categories are arranged in descending order of that frequency values.
And this line is showing the cumulative relative frequency values.
For example, the relative frequency of this category is around 35 percent.
When I add the second category, it becomes nearly 70 percent of the third category.
It becomes nearly 88 percent.
After adding fourth category, it becomes nearly 95 percent.
And the last category acts it to 100 percent.
So using Perito, you can estimate how many of these categories contribute to how much percentage of
the total.
So, for example, if you would like to find out those important two or three categories, which are
going to be 80 percent of the total, you can do that using a burrito analysis.
So this is how we create frequency distribution and histograms.
Good thing about using Excel is you do not need to create a frequency distribution table to create a
histogram.
I told you how to do that so that you understand the concept being a histogram.
That's all for this video.