I use these videos as examples to solve my assignments. If it was not for this man, I would have dropped my statistics class long time ago. Thank you man for saving me from failure
I put exact numbers into my excel. So, you're .06 for P^2 is actually .064. When you use .064 instead, you get a Z-crit of -1.9754 which is in the "reject" zone. So, there is significant evidence to support this claim.
p^ is just the number of defects in the sample divided by the sample size, so p^2 = 30/500 = 0.6. The poster of the video is correct. You probably messed up something in your Excel sheet.
Hello, two separate questions derive from this example, (1). Is the hypothesis testing and the formula still valid if the two groups were actually overlap? Extreme case would be the second group of 500 laptops were all in the first group. (2). Is the hypothesis testing and the formula still valid if let's say we want to see if the battery defect in group one is significantly different then the monitor defect in group two (assuming the proportions still be 32 out of 800 in group one and 30 out of 500 in group two).
in this kind of exercises i can never understand what to subtract first. If we have even two difference mean what should i subtract first? and then make the hypotesis
The difference between my professor and this teacher is that my professor makes it look more complicated while this teacher keeps it very simple and easy.
Replace x with the value that you want to convert, y will be your answer. Fahrenheit to Celsius formula: (x°F − 32) × 5/9 = y°C Celsius to Fahrenheit formula: (x°C × 9/5) + 32 = y°F Fahrenheit to Kelvin formula: (x°F − 32) × 5/9 + 273.15 = yK Celsius to Kelvin formula: x°C + 273.15 = yK
To get the left alternative area... So we can get critical/observed Z-value on the table...we don't the calculated Z-value then compare the two to draw your conclusion. There's a different method P-value method if you don't like this one
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Someone give this man a Nobel Peace Prize already.
Sorry, no
You know that there are Nobel Prizes in science, right?
I use these videos as examples to solve my assignments. If it was not for this man, I would have dropped my statistics class long time ago. Thank you man for saving me from failure
I wish you'd do more of there... you'd help alot! Thanks as always
saving my master's degree in clinical psychology, bless you forever and ever and everrr, thanksssss
From AP Calculus in high school to now college statistics, this man saved me a thousand times!
you are massive. Great help do you offer. Bless you a million times!!!
You are so very awesome. You have helped me a lot. I think that all of your videos are simple and super easy to understand. Thank you so much.
Bro I was looking for this question everywhere thank you so much
Thank you so much for saving me from stats like I really mean it.
Your channel is such a saviour
Thanks!
Why dont i meet such lecturers in my life? My poor background of Maths🤦♀️has come back to haunt me in biostatistics.
Just calculated what I think is a significant result for my dissertation. Thank you so much! 😄
Ive learned more from this man than ant math teacher could dream of
I put exact numbers into my excel. So, you're .06 for P^2 is actually .064. When you use .064 instead, you get a Z-crit of -1.9754 which is in the "reject" zone. So, there is significant evidence to support this claim.
p^ is just the number of defects in the sample divided by the sample size, so p^2 = 30/500 = 0.6. The poster of the video is correct. You probably messed up something in your Excel sheet.
I have also done the same question and it falls in the reject region.
Hello,
two separate questions derive from this example,
(1). Is the hypothesis testing and the formula still valid if the two groups were actually overlap? Extreme case would be the second group of 500 laptops were all in the first group.
(2). Is the hypothesis testing and the formula still valid if let's say we want to see if the battery defect in group one is significantly different then the monitor defect in group two (assuming the proportions still be 32 out of 800 in group one and 30 out of 500 in group two).
Request you do video of inference about more than two population means:ANOVA
in this kind of exercises i can never understand what to subtract first. If we have even two difference mean what should i subtract first? and then make the hypotesis
Yes I was wondering, lol thank you
Why do we use A_l of 0.975 and not 0.95 since we are not interested in what direction the two proportions differ?
The difference between my professor and this teacher is that my professor makes it look more complicated while this teacher keeps it very simple and easy.
your pooled proportion part of your equation is showing P-hats. Shouldn't it be P-bars?
You’re great ♥️
My go to guy👌🙌🏾🔥🔥🔥
You are really awesome 😌
Thanks 😊
Hey Prof, but how is Zc derived? I can plug in numbers and get the result but why does the formula look so funky?
Can you please tell the method's definition as before applying the formula I require to explain about it in my thesis?? please
check out jbstatistic, he does explain the definition and dive deep into the theory first
Thank you bro
for the first example, what if we want to use binomial distribution?
How did you get the 0.012149 ? Please respond im so confused😭😭
you saved me from an F on an exam thank you!!!
Can you do a video on how to convert fahrenheit to celsius, Celsius to fahrenheit, fahrenheit to kelvin and celsius to kelvin?
Replace x with the value that you want to convert, y will be your answer.
Fahrenheit to Celsius formula:
(x°F − 32) × 5/9 = y°C
Celsius to Fahrenheit formula:
(x°C × 9/5) + 32 = y°F
Fahrenheit to Kelvin formula:
(x°F − 32) × 5/9 + 273.15 = yK
Celsius to Kelvin formula:
x°C + 273.15 = yK
Receive your flowers while you can smell them 🎉😊
Typical UA-cam guy saving my ass a day before the exam.
why did you add .95 + .025?
To get the left alternative area... So we can get critical/observed Z-value on the table...we don't the calculated Z-value then compare the two to draw your conclusion. There's a different method P-value method if you don't like this one
What if you don't have n2 and x2?
Bit late now but then it is just a distribution model or a hypothesis test and not a proportion test
Can you do the z table on a calculator because we dont get a table we have to use a calculator for us it's the ti-inspire
Im sorry lord
you cant use your calculator for z table you have to have that table
how can i do this in R programming?
Bro 30+32 ; 500+800 ; 62/1300=0,047 < 0,05 so its still no problem.
This motherfucker using that limited edition statistics
Thank you haha
statcrunch guys this is unnecessary.