Hi
Welcome to the interview
This video is based on the biostatistics chapter on the path textbook of Community medicine
Now the basic biostatistics needed in your medias can be divided into these broad heading I
Will be dealing with the first three in this video
The next four topics will be covered in a second video
The remaining extra topics will be covered in a third video
So the first topic is data presentation
We all know that data can be subdivided into two categories
Quantitative and qualitative
So now we will discuss about the various ways to present
quantitative data
first this histogram
The histogram is a graphical presentation for continuous quantitative data
The continuous groups are plotted on the x-Axis and the frequencies are marked on the y-Axis
next comes frequency polygon
It is similar to a histogram
Except that it is smooth by joining with points of class intervals and the heights of frequencies
Next is a frequency curve
it is basically a frequency polygon that has a number of observations and
reduce groups interval
Hence the Angles are smoothing and it becomes a curl
Next is a line chart it is also known as a line graph
It shows a trend of an event over time
Next is cumulative frequency diagram it is also called ogive
It is a graph of cumulative relative frequency distribution
finally the scatter diagram
Hot-dog diagram it is also called correlation diagram because it is used to detect
Correlation between two variables I
Will be coming back to scatter diagram in a minute
This brings us to the end of the quantitative methods of data representation
Now we talk about the qualitative methods of data representation
First is bar diagram
it is used for visual comparison of
Magnitude of difference frequencies it is considered to be the most
versatile a whole scatter dance of all particular grams
Next comes by offsets a diagram here
The Categories are represented as a percentage of the total hundred percent
But remember for pie diagrams all pie categories must be usually exclusive
next this picture diagram
Or pictograph it is a method of data in presentation for the common man to understand
So it often contains pictures
Finally then slab diagram or spot map it is prepared to show job fiscal distribution of frequencies
here each dot marks one frequency
This completes the methods of data representation
Now coming back to scatter diagrams
We have understood that it is used to direct
Correlation but how
Look and the diagram of them on the left
Here the dots arranged in such a manner that their average forms a straight line. Whose slope is positive
This slope is the Correlation coefficient R
When the correlation coefficient R is equal to plus 1 then it is called positive. It's correlation
Love look at the diagram in the middle
Yes, the dogs are arranged in such a manner that their average forms a straight line. Whose slope is negative
So R equal to minus 1 and the correlation is said to be negative
Finally look at the diagram on the left
Yes, no line can be drawn because the dots are any diffusely, so there is no correlation
next we come to the topic of variables a
Variable is a character or attribute that varies from person to person and some time to time
So variables can be divided into quantitative and qualitative
Quantitative variables as a ones that can be measured directly on a metric scale
example weight height without response or
Qualitative variable for the ones that cannot be measured hence they have a nominal scale
typical examples include abo blood group sex and type of any meal
If you are wondering, what is a nominal scale don't worry? I'll be discussing both the skills types of scales in alone now
quantitative variables can also be called continuous variables
Why?
because they have a large number of possible values and
Several in-between one so they are measured in a metric scale
but
Qualitative variables only have a few possible values and lonely between values and they are also called
discrete variable
variables can also be subdivided into dichotomies and call your own of x
dichotomous variables have only two passive possible values
Whereas all umizoomis variables has more than two possible values
Typical example of dichotomies available is sex it can only be male or female
Another with erect it can only be positive or negative
The examples of polyatomic variables are in silent
This brings us to the end of the topic of variables
Finally we come to scales of measurement
They are basically three scales of measurement
Number one is log Roadkill number two is ordinal scale and p is much equal
Nominal scale is based on nose. It has no specific order and for quantitative variables and
Is for qualitative variables?
typical examples include the Religion Country Etc
Ordinal scale is based on gradation. It is also for qualitative variables
typical examples include the MMCD cushion glasses Etc
finally
Matrix scale in the scale we use regularly on our day-To-day life for measurement of quantities as
I just mentioned it is for quantitative variable
Unless the type of scale is also read. It is called likert scale or somatic scale. This is a type of ordinal scale
Here the responses are graded in a continuum like strongly disagree disagree
Slightly differently lightly as we agree and strongly agree
Also like this case is usually by polar scale rule it measures both positive and negative
responses
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