Tutorial 19- Type 1 And Type 2 Error In Statistics-Krish Naik Hindi

[@Rosh12373]

Type 1 : occurs when the null hypothesis is rejected when it is true Type 2 : occurs the null hypothesis is accepted when it is false

[@VickyPatel1293]

You can easily understand this concept by considering an example... Let's assume we are assessing whether a patient has cancer or not. If our model predicts a positive result, but in reality, the patient does not have cancer, it is a false positive (Type 1 error), which is not harmful in the case of cancer. However, if the model predicts a negative result, and in reality, the patient has cancer, it is a false negative (Type 2 error), which is very detrimental to our model. Therefore, our focus should be on reducing this specific misclassification error.

[@AkashSharma-ij4sn]

this is understandable but the way he created the relation with confusion matrix to conclude type1 and type2 error thats not clear

[@harmeeksingh2320]

Sir you have no idea how good you are as a teacher, this playlist has really helped me to learn a lot about the Applied Statistical Analysis. I request you to please complete this playlist. Thank you very much. Keep up the good work.

[@SaurabhSingh-sy1pe]

@12:15 it will be type 2 error or False Positive @13:59 it will be type 1 error of False Negative

[@AjitKumar-fs9lc]

Oh bro thank you , I've been confused for the past 30 minutes yaar.

[@hairavyadav6579]

Mai v confuse ho gya tha

[@somanshgirdhar4239]

he is right in this part but opposite in initial 2

[@sanch6239]

Krish sir, I think "Outcome 3 = FN(Type 2 Error)", & "Outcome 4=FP(Type 1 Error)". But in video you said vice versa. Please check it once again.

[@suronitachandra5791]

Yes also I think so

[@OBECEOODishantKorat]

yes, you are right. he made a little mistake. Type 1 : occurs when the null hypothesis is accepted when it is false Type 2 : occurs the null hypothesis is false when it is true

[@jaykishan3633]

SuPPerbbb explained Sir...

[@Chandra366]

😮 Thanks sir...

[@ashushukla8879]

in 12:05 you said in prediction it is false(0) and in reality it is true(1) then it should be FN but you take it as FP. please clarify

[@kumarkirti4438]

Yes it should be FN

[@SumanSadhukhan-md4dq]

Yes you are right it should be FN

[@physics3603]

Please sir help me to solve this confusion or some one please please explain if I am wrong 3:31 yaha pr aapne kaha he ki , FP(i.e predicted true but in actual it is false) is type 1 error and FN(i.e predicted False but in actual it is true) is type 2 but here 12:28 , you say that we rejected the null hypothesis but in actual it is true that means it becomes FN sir , so It should be type 2 error but you say that it is type 1 error

[@ankitprasad1407]

you are right bro, sir mistakenly switched the error types

[@baithak3438]

Your FP and FN need to reverse in confusion matrix . They r causing real confusion .

[@sagardeepsingh5151]

true

[@hsk7715]

Confusion matrix kafi confusing hey

[@nayeemx11]

please complete full statistics for DS/ML

[@ShakiraGCET]

Hello Krish after completion of this course will you help us in interview process also

[@ZibaFact]

Thanks 😊👍🏻

[@user-hl9tc9qg3w]

Thank you sir

[@rajkumardubey5486]

To reduce this type 1 and type 2 errors is there any other way to reduce it other then hyperparameter tuning, threshold value adjustment

[@ZibaFact]

Good question

[@DaytoDaylifechain_wow]

Brother 1 thing is wrong that you consider (0)of actual instead of predicted so basically outcome 3 should be FALSE NEGATIVE

[@sumitsaxena7245]

great knowledge

[@bitknowledge.2493]

❤

[@punitbhadayuia]

Type 1 and type 2 error in your confusion matrix diagram is interchanged. Please edit and do correction. This decreases our confidence in your videos

[@alopsingh4772]

dimang ki upar se gya

[@VickyPatel1293]

mera comment refer karo shayad aapko help karega confusion matrix samajh ne me

[@Shivam-st4kq]

Are ye faltu padata hai

[@ShivKumar-yr2rn]

❤