In this video, we are going to learn how to do univariate analysis in Microsoft Excel, as I told you,
in detail related.
We want to look at some summary statistics like mean median mode of all the quantitative variables.
To do that, we use data analysis then in Excel.
You can find the data analysis and data menu if you are not able to see this data analysis option,
you need to go to the file menu, click on the options button here.
You have to go to Alden's.
In the bottom, you have to click on Go Button, which is for many excellent.
Hair analysis tool that should be paid if testing you, you'll get this data analysis and then you determine
if it is not, you will not see this.
So take this and click on.
Before we use the data analysis again to do univariate analysis, we need to segregate the quantitative
and qualitative variables.
As you can see in our table, we have several qualitative variables, such as airport, water, body.
And Buster.
These variables are categorical, they do not have numerical values in them.
We will take all these categorical variables and put them in the end of the data.
They will.
So we'll select the whole column by clicking on the name of the column, pressing controllers to cut
and control, we in the end to pasted.
We will do the same for the other columns.
This is the last categorical column now these blank columns will be deleted.
Just right, click on the name of development, select delete.
So all are quantitative variables are from column B to column Q, the columns are these are having categorical
variables.
So now we will go to data analysis here.
We will select descriptive statistics.
This is the option we need to select to do univariate analysis will click on OK.
We will select the whole input range from B three to two five zero nine.
You can see the shortcuts on the bottom right of the screen, which popped up when I pressed them.
So important.
And the next option is group by here we have to select the option where we have our variables, since
our variables are in the columns and our observations are in rows, we want to group them by the columns.
Next option is Labor's infrastructure, since our table contains Labor's infrastructure, that is the
name of the variable is in the first row of the table.
Therefore, we will take this checkbox.
Then is the option that where do we want the airport to be placed?
We want the airport in a new wheelchair.
Therefore, we have selected new Wilkshire.
Then is a check checkbox for some of these statistics.
We will take it since we are doing univariate analysis and we do want to see these summary statistics.
The last two options will be used to get the cartel values, since by default, descriptive statistics
option is not going to give us the cartel values, we will put 25.
In both of these.
So the 25th smallest value is actually the first quartile value, that is the 25th percentile value
and this twenty fifth largest value is going to be the 75 percentile value of the third quartile value.
So with all these options, it will just click on, OK?
And you can see in a new sheet I am getting.
The descriptive statistics of all the quantitative variables.
Here you can see the mean standard median mode, standard deviation.
The Bulgarians and other such values.
The point of looking at this descriptive statistic values is that we want to identify the problems in
our dataset, a dataset can have several types of problems.
One problem could be of missing values, for example, some variable, maybe missing a few of the values
from its data.
One problem could be of outliers.
That is some variable maybe containing extraordinarily large or smaller values, although we will see
how to identify and handle these problems in the coming videos here.
We will see how to identify these problems using the descriptive statistics we have with us.
So to identify if any particular variable is missing some values, we can use this control, all the
variables should have the same goal.
That is, since we have 506 observations inaudible, all the variables should have 506 values.
If any variable is missing some values, it will have a lesser count.
We can see that for the variable and hospita.
We have got less than five or six, it is brain.
This means that it values are missing for this particular body will we will see how to go and rectify
this in our dataset.
The second problem would be of outliers.
To identify outliers from Italy, there are two possible ways, one is to look at the difference between
mean and median.
So if there is an outlier, suppose we have an exceptionally large value in some variable.
So far, such a variable demesne will be shifted towards the outlier and median will remain almost at
the same range.
So there will be a large difference between mean and median values.
The second method is to compare the distribution of the variable between different coordinates.
To compare the distribution and content, we will see the difference between smallest and the first
quartile value and the 70 percentile and largest value.
So if I look at this price variable.
The mean and median are almost in the same range.
I mean, is twenty two point something and median is twenty one point something.
If I look at the quarterly distribution, the first quarter is between minimum and the 25th percentile
value, the minimum value is five and the 25th percentile value is ten point two.
So in the first quarter, we have a range of five point.
In the last quartile, the seventy fifth percentile values, forty three point eight, and the largest
value is 50.
So the last quarter has a range of six point to.
So the difference between the Quartel distribution is not very large.
This is suggesting that price, well, does not have any outliers.
So I will highlight this very well, which actually has some outliers.
If you look at the Anholt rooms very well.
From the mean and median value.
There is not much different.
Which may tell us that maybe there is no players when we look at the Quartel distribution, the first
quartile is ranging from ten point zero five to ten point one, which is a very small range of point
one.
And the last quarter is ranging from fifteen point one nine to one hundred one, which is a very huge
range of eighty five unit, so definitely there are some outliers in this particular variable.
How to handle all players will be seeing in a separate letter.
So this is how by looking at the entity, we can identify problems in different variables, I suggest
that you go through each and every individual variable to identify the issues with that variable.
Later on, we will learn how to handle each of these issues.