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Hello, all so in all our previous session, we have done some interactive analysis, so in this session

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I'm going to have this assignment in which I have for of the statement, which is somehow related to

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our hypothesis analysis.

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So the very first one is I have to consider two hypotheses depending upon what statement I have.

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So here I have the age of a person is going to be a factor in available loan or not.

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And then I have to automate all the stuff.

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So these are basically my advanced kind of analysis.

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So here I'm going to show you how exactly you can perform all this stuff in a very simplest way.

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So very first, I'm just going to call it scatterplot on my data points, on my features.

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Here I'm going to say I have to float a scatterplot between age and, of course, between personal loan.

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You will see this exactly is my personal loan.

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So just start over here.

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And this is exactly personal loan.

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And let's say you have two data points on the basis of, let's say, family.

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So here I'm going to say split it on the basis of Ramla.

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So if you are going to execute it now, you will see your beautiful scatterplot and here you have family

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status as well.

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So now you have to simply perform your hypothesis.

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So to perform your hypothesis, you have to import some of the library, because this is exactly part

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of scientific by time so far this you have to import your Sappi module.

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So here I'm going to say just import side by dot instead.

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And let's say I'm going to create ideas as let's say instead just executed and using this instead.

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So it is saying, yeah, it's not side by side by.

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So again, executed and using this instead you have to perform some kind of test over here depending

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upon your number of samples.

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So very fast.

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And is will define my two hypotheses over here.

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So if you're not over to the basics of hypotheses, the different types of T-test, I would recommend

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you to go to the back of this video and just clear your basic spec until I have uploaded a lectures

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on hypotheses as well as on the test.

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So very first I would define my two hypothesis.

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Let's see.

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The first one is my null hypothesis.

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So here I'm going to say my null hypothesis is basically, let's say age doesn't have impact on available

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personal loan.

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So my alternate will be reverse of this.

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And at that point, only one can be true.

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So let's say my alternative achey or you can be presented as well.

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So this is exactly my alternate hypothesis.

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You have to present it and you have to just remove this.

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Not so.

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This is exactly my alternate hypothesis.

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And now that if you need some data, you need some sample.

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So here I'm going to say very first, I have to access my personal loan.

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This one.

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And the very first condition is I have to access all the data where my personal loan equal to zero.

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So this is exactly my entire data.

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And on this data frame, basically I have to access the each data and let's say to convert it into array.

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I have to just call umpired or add it to convert all this stuff into.

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So this is exactly my very first edit.

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You can copy it, you can paste over here and that's it.

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At this time I want for Ajita having both the loan equal to one.

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So here I am going to say this is my let's say on underscore no.

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And for this, let's say I'm going to see it on this call.

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Yes.

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So just executed and now your data is ready for your.

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So just showing me gonged Azania here I have to assign underscored not a constant.

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So now my data is ready, my sample is ready to perform to sample data.

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So why does Hanbali test.

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Because here I have two samples.

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The very first one is my agent Schorno, and the second one is, of course, my age on the score.

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Yes.

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So two sample T dead will basically give me a quick overview of.

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Yeah.

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Whether there is a statistical difference between the mean of the board, the samples or not.

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For this, I have to call some of the functions from my steps, so for this I'm going to say, is that

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deep test not BASTABLE over here?

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You can get your data underscore I and the surpass shift plus tab.

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And here you have to pass here and B, which is exactly my data, which are exactly my sample for the

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very first one is exactly my age under called No.

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And the second one is exactly my age and a score.

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Yes.

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And now you have to pass your access parameter as well.

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And so it will basically told me to value the first one is my D and the second one is, of course,

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my B value, so that I'm going to say this is my business value and the first one is my destiny value.

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The second one is my P value.

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And P value is the most important value in this case.

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For now I'm going to say I'm going to simply put a condition over here and here.

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I'm going to say if P value is basically less than zero point zero five.

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So this is my condition.

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So in such case, I can say I have to print my this alternate hypothesis because then I will be valued

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less than zero point zero five.

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In such case, I have to reject my null hypothesis and to zero, which is exactly my null hypothesis.

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That's why I had to reject this.

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So now in the printed statement, I'm going to say I have to reject this at Ejiro and accept this edge.

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So very first, let's say I'm going to print this very first Etch A and after it, I'm going to say,

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as the P value is basically less than zero point zero five with the value of whatever value of B, I

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will get over here for here, I'm going to add placeholder and this time I'm going to add my format's

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function.

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And whatever placeholder here, it will basically receive value from this format.

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So here I'm going to say B, underscore value, whatever P value this will return.

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So this will get over here.

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And now in Ellsburg, basically I have to add a condition.

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So in Allsburg, my value will be greater than zero point zero five.

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And in such case, I have to print, let's say, at zero.

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So this time I'm going to say print, just print at zero.

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And now I have to print all this stuff together.

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Then here I have to say p value is basically greater than zero point zero five with a value of whatever

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value will be there to just execute it.

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And you will see it will reflect me.

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It doesn't have impact on our valving.

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Personal loan as a P value is greater than zero point zero five.

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It means our P value is basically greater than zero point zero five.

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It means this condition will come in this block.

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This as well.

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And if this will come to us, blog might as zero, which is this one, this will get printed and then

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this blocks of code will get printed with P value, whatever P value I will get receive from here.

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So this is how exactly your all loop will work over here.

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So let's move to the next problem statement in which I have to automate this hypothesis.

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I have to automate this stuff.

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So for this, let's say I'm going to say I'm going to define my function.

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Let's say the function name is hypothesis.

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So this function name is hypothesis.

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And now this time, whatever code I have written over here, I have to just import it.

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So very first, let's say I'm going to say I have to just import all this data.

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So here I have to pasted.

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And after that I have to also copy from here.

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So now this time I have to pay as well.

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So provide right indentation over here, here, here and here and here as well.

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So now in Sinéad use deadly force.

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I'm going to say columns on the second one is of course my column too.

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And then let's say you have to assign some of the hypotheses as well.

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So now I'm going to say my hypothesis is, let's say at zero and the first let's say at all, and the

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first one is my actual and the second one, which is.

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My alternate hypothesis I would represent it is Etch A and personal loan will get replaced by basically

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my columns on similarly over here, my personal will get replaced by column one.

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Similarly, this will get replaced by column two.

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This will also get replaced by column two.

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And now here you have to pass your added one and add it to let's say this is exactly why I added one

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and let's say this is exactly my added to and here I have to pass both the add over here.

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So the very first one is exactly why added one and the second one is exactly my area.

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So it will return me my details and my P value.

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And this is exactly my condition or what you can do, guys.

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You can simply put all these blocks of code in print and it will basically receive value from, let's

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say, a formula function similarly for at zero as well.

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So just remove this and now you have to write over here as at zero or you can write here as a placeholder

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and whatever value it will receive.

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So here I'm going to say it is my exactly at zero comma P-value and here is my achee.

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So similarly here you have to also assign your placeholder as well.

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So just executed.

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And now it is showing me Indentation Adder because here I have some in addition.

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And so you can provide that indentation.

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Similarly here provide right indentation because in addition added the will of course happen in Python

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if you don't provide right.

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Indentation.

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So now you have to just call this function.

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So here I'm going to say just call this function using hypotheses and just shift plus tab.

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So that column one is basically my personal loan.

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So here I'm going to see my personal loan is exactly my first column.

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And on the basis of column, do I have to assign this each column and now I have to assign my alternate

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hypotheses as well as null hypothesis.

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Let's say the first one is exactly my null hypothesis, and this is exactly your null hypothesis.

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Or you can copy from here.

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And let's say I'm just going to paste over here and now it's time for your alternate hypothesis.

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So although it will be this one and just copy from here and you can paste over here all these stuff

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to just execute it and it will give you a solution at age.

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Doesn't have impact on availing personal loan because here you will see your P value is greater than

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zero point five.

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That's why you have this type of confusion over here.

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So how exactly will see this is a power of the automation.

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You have a just call this function and you have to write this docs of code.

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You don't have to write it blocks of code again and again.

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Let's say you have to perform this hypothesis for.

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Yeah.

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Does income of a person have an impact on a willing loan or not?

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So what you have to do, you have to just copy this.

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Let's say I'm just going to copy this entire code and I'm just going to paste over here.

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And now I have to just play with some of the parameters.

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So here I'm going to say the first one column is exactly my personal loan, or you can assign it as

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well.

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So this is exactly my column one.

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And now in case of column two, I have, of course, my income.

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So I'm going to say income.

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And now on my null hypothesis, I'm going to say income doesn't have impact on availing personal loan.

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And in alternate, of course, I have income will impact.

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So just execute it and it will say me.

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Yeah.

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Income impact on the available personal loan, because here you will see your P value is somewhere close

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to zero.

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So if you are going to plot this scatterplot between personal loan and income, you can simply rely

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this effect of yeah.

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Why income has an impact on availing Boston law in a similar way.

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You can also do hypothesis for this one as well.

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We are the family side makes them do our loan or not.

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So just copy paste here.

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And in column one, I have, of course, my personal loan, but in case of it, I have basically my

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family.

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So here.

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I'm going to see my family and now here I'm going to say family doesn't have impact on of any personal

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alone wedding.

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In case of alternate hypothesis, I will say your family will definitely impact.

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So just execute it and you will see it.

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Will see my family will, of course, impact on our wedding lawn because you will see your P values,

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of course, approx to zero.

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You will see one point four into E to the power minus five.

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So it will be very nil value.

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That's why it is showing me our family have I impact on a really personal note.

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So I hope you will love this, all this analysis, how I'm going to automate all of this stuff rather

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than writing all this course again and again.

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I'm just going to call this function or if you want to play with it, what you guys can do.

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You guys simply autodidacts of code in your hypothesis function.

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And once you have this printed statement, you can also get your visual as well.

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So that's a pretty cool way.

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How exactly you can analyze your data.

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So hope you will love this analysis.

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Thank you.

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How nice day.

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Keep learning.

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Keep going.

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Keep practicing.