Logo

Stat 88 class - Shared screen with speaker view
joel chang
17:57
Yessir
Sophie Liu
17:58
yes
Brendan Co
18:00
yup
isaacecheto
18:00
yep
Nishi Rahman
18:05
yes
Rebecca Hu
20:35
1 - phi(7.23)
isaacecheto
20:37
Still working on it
Dayne Tran
20:42
its the binomial summation of p(x>134)
michellecan
20:51
^
isaacecheto
20:57
^
Zachary Zhu
21:08
phi((134-100)/sqrt(300*1/3*2/3))
Naqeeb Punjani
21:10
^^^
Zachary Zhu
21:21
1- that
ashley minooka
25:25
why is it 8.2**2 again?
isaacecheto
25:34
That’s variance
Jooee Karwande
25:36
Why couldn’t you have done the binomial summation?
isaacecheto
25:36
Not SD
Joshua
25:53
I’m doing well
Nishi Rahman
25:55
Can you explain what k is again?
Dorkhan Chang
26:21
It is normal because 300 is large enough right?
Michael navruzyan
26:21
can you explain again why you can use normal approx
Nishi Rahman
26:24
Thank you
Shannon
26:46
what is "large enough" generally?
isaacecheto
26:58
µ - 3SD > 0
Alex Xi
27:41
how do we find the probability if its within 3 standard deviations?
Laura Nguyen
27:43
is attendance actually mandatory?
Brendan Co
27:53
Lol ^
Forrest Kim
27:58
gotteeem
celinewherritt
28:04
Lmao lauras famous
Monse Lopez
28:24
How do you know there is no data at 4 sd?
Alex Xi
28:38
how do we find the probability if its within 3 standard deviations?
Matthew Simon
28:49
How do we know it is still shaped normal because couldn’t its shape be really strange but still meet those 3SD parameters?
Marisol Trejos
28:55
Why did you use P(X>=135) and not P(X>134)
Monse Lopez
29:01
thank you!
Alex Xi
29:14
ok thank you
Matthew Simon
29:51
Yes thx
Marisol Trejos
30:26
ys
sophia
30:57
Can we still put P(X>134) though?
lucy sandoe
36:13
what do you mean by "at T"?
Shannon
37:06
It's "of TS", I think
Kaci Gu
41:07
is the p-value equivalent to the sd(x bar)
Noah Wadhwani
41:13
What exactly does phi represent again?
celinewherritt
41:43
Why did you divide by root 150 again?
Jooee Karwande
42:06
That’s the formula for SD(average)
lucyzhang
42:06
Why did we shade the area towards the right again
Kaci Gu
42:26
Got it thanks
Marisol Trejos
42:30
How did we get 299,796 as the X(bar)
lucyzhang
42:38
Yea!
Marisol Trejos
43:11
Yes thanks
Michael navruzyan
43:30
why is 50 not sd of sample mean
Joshua
43:56
Why do you do 1-phi? Instead of just phi
Nishi Rahman
45:15
What does phi mean again
Joshua
45:16
yeah
Joshua
45:27
Is there a case you would just use phi?
Nishi Rahman
45:44
And you multiply that by .87 to get standard units?
Joshua
45:46
Oh that makes sense
Nishi Rahman
46:09
oh
Nishi Rahman
46:15
okay
lucyzhang
49:48
For Ho, can u simply say that the data supports the hypothesis that the unknown mean 98.6 is normal temp? So basically restating the question
Joshua
50:53
Isn’t it supposed to be 98.6-98.2?
Michael navruzyan
51:59
is it p(x bar < 98.2) or p(x < 98.2), what's the difference?
Monse Lopez
52:35
do you use sd of x bar to account for error?
lucyzhang
52:37
Do u say accept or fail to reject
Marisol Trejos
53:11
I usually say fail to reject
Joshua
54:21
Oh yeah gotcha
Matthew Simon
54:29
Can you go over again the difference between SD of x bar and SD x
Kieran Cottrell
54:53
Is there a way to test for both sides of X instead of just doing a one sided test
Michael navruzyan
55:44
yes thanks!
Monse Lopez
56:44
yes! Thank you
lucyzhang
57:44
Got it, thanks!
Newton Szeto
58:17
how do we calculate the numerical value of phi((98.2-98.6/0.15))?
Matthew Simon
58:29
Yes thx
Newton Szeto
01:00:01
Thank you!
Joshua
01:08:18
Did you assume those two probabilities were equal to each other because a large n assumes a normal distribution?
isaacecheto
01:09:39
Yep
Michael navruzyan
01:10:35
if you use X bar as TS, what would sd(x bar) be?
sophia
01:11:19
Why do we reject when X-266 is LARGE?
lucyzhang
01:11:21
Can u also do 277-266 and times 2
Joshua
01:11:37
^
lucyzhang
01:11:54
And what does T is large mean, how large is large
isaacecheto
01:11:57
Sophia we accept because it means that the observed statistic being only 11 away is probable
Joshua
01:12:16
You answered it early
Nishi Rahman
01:12:23
Where does 277 come from?
amywang
01:12:25
Why isn’t it just the P(X<255) since 255 is the observed statistic? Why do you check the other end too
amywang
01:12:56
^yeah why do you also check 277
Monse Lopez
01:13:21
Nishi the 277 is from the observed values given to us at the beginning of the problem
Michael navruzyan
01:13:56
yes thanks
sophia
01:14:31
yes thanks!
Nishi Rahman
01:14:44
Thanks Monse!
YeJin Ahn
01:16:04
Why do we accept the null because 0.44 > 0.05?
Newton Szeto
01:16:43
where do we get the numerator of SD(x bar)?
Nishi Rahman
01:17:19
yes
amywang
01:17:22
Oh my question is where does 255 come from then
amywang
01:17:26
Since 277 is observed
amywang
01:17:54
Sorry I asked my question in correctly
Marisol Trejos
01:18:54
Why dont we subtract 1-2phi((255-266)/14.1)
sophia
01:19:27
Did we assume that P(X>277) = P(X<255)?
YeJin Ahn
01:21:03
Thank you professor! :)
Newton Szeto
01:21:27
Yes
Newton Szeto
01:21:49
Yes
Newton Szeto
01:22:00
Thank you!
Matthew Simon
01:22:03
So when do you use square root of npq
sophia
01:22:21
SD of Binomial
Nishi Rahman
01:22:38
Can we go through finding the p-val with x bar as a T.S>
lucyzhang
01:23:09
Do we always have to do two tails?
Marisol Trejos
01:23:41
Okay
Marisol Trejos
01:23:45
Thanks
Marisol Trejos
01:23:55
yes
sophia
01:24:19
Thanks!
sophia
01:24:27
YES!
Matthew Simon
01:24:58
Got it
Matthew Simon
01:25:07
Yes thank you
Michael navruzyan
01:27:24
so if its a sum why don't we multiply the 14.1 for SD(x) by sqrt(n) to get sample sum sd
Michael navruzyan
01:30:44
ahhhh
Michael navruzyan
01:30:49
thanks so much
Monse Lopez
01:31:03
sorry I still can’t wrap my head around how we come to the conclusion
Monse Lopez
01:31:10
Can you explain again?
Monse Lopez
01:31:24
yes
Monse Lopez
01:31:50
By extreme you mean small?
Monse Lopez
01:32:02
oh yess
Monse Lopez
01:32:23
Ahhh yes
Monse Lopez
01:33:03
yes thank you!
Nishi Rahman
01:33:07
What is the argument when we calculate phi in python? stats.normal.cdf(____)?
Monse Lopez
01:34:21
nope thank you!
Shannon
01:34:29
thank you!