Andrew

11:38

prof, you're echoing a lot on my side

lucy sandoe

11:43

^

YeJin Ahn

11:49

^

Marisol Trejos

11:49

^^^^ same

Jooee Karwande

11:51

^

isaacecheto

12:44

yep

Joshua

12:45

yup

Shannon

12:46

yes

Jooee Karwande

12:47

ys

YeJin Ahn

12:48

yes

Joshua

13:10

yes

chelsie

13:10

yes

Andrew

13:11

its fine now

Jooee Karwande

13:12

The echo is gone

Shannon

13:13

yes

YeJin Ahn

13:13

yes

isaacecheto

13:16

It’s not echoing anymore

lucy sandoe

14:19

5%?

Vasanth Kumar

14:27

- phi(.05)

celinewherritt

16:15

Do u use ppf for these examples bc it gave u a 90% percentile?

lucyzhang

17:09

Can u not use inverse for b? Is that an option?

lucyzhang

17:24

Wait nvm

lucyzhang

17:28

thanks

Dorkhan Chang

17:29

for a, wouldn't inverse of (0.95) also give you area to the left of "-z"?

Zachary Zhu

18:32

~68%

Marisol Trejos

18:36

68%

lucyzhang

19:49

Sorry when do u use inverse and when do u not?

Joshua

22:12

Is the empirical rule strictly for normal curves?

sophia

31:41

Can you explain z > 1.9 again plz

sophia

32:20

yes you said something like 1.9 SD away

sophia

32:28

From 0?

sophia

32:57

got it thank you!

lucy sandoe

34:09

sorry what does i.i.d. stand for?

lucy sandoe

35:58

thanks

Jooee Karwande

36:55

Are we supposed to know what phi(1.25) is

sophia

37:07

On the quiz can we leave our answers in phis

celinewherritt

37:38

Why do we multiply the SD by root 100 not 100

Alex Xi

37:45

^

lucyzhang

37:46

Why did u do sort root of 100 *2 again

lucyzhang

37:51

square

celinewherritt

38:08

Ohhh ok thank u

lucyzhang

38:12

Okay that answered my Q thanks

Stephen

38:15

Must start with transformation of variance

Stephen

38:25

Then square root

lauraherron

39:46

b

Jooee Karwande

39:47

b

ashley minooka

39:48

b

Marisol Trejos

39:48

a

Atmika Ashok Pai

39:48

b

lucy sandoe

39:48

b

Zehra Ali

39:49

b

jessicaornowski

39:49

b

chelsie

39:49

b

mayareuven

39:49

b

louisnorris

39:49

b

Noah Wadhwani

39:50

b

Zachary Zhu

39:50

B

celinewherritt

39:50

b

sophia

39:50

b

Kieran Cottrell

39:51

b

Lauren White

39:51

b

Vasanth Kumar

39:52

b

YeJin Ahn

39:53

b

Natalie

39:54

b

Ronan Figueroa

39:55

b

Laura Nguyen

39:56

b

Justin

39:57

b

Dayne Tran

40:01

c

Micah Grim

40:03

b

Michael Madden

40:05

b

sophia

40:51

Why can’t we use CLT?

sophia

41:49

got it

Brendan Co

48:59

no

Jingyu Han

50:27

where did you get -1.645 again?

Jingyu Han

51:14

Oh I see

Jingyu Han

51:31

yup

Jingyu Han

51:32

Thanks

Dayne Tran

54:39

hi for markovs isn't it greater than or equal to, so should the p be p(x >= 701) and we use 701 in 690/c?

lauraherron

54:46

how is the probability over 1?

Dayne Tran

55:59

yes thanks

Stephen

56:00

how do we know when a distribution is discrete or continuous?

parkersalomon

56:21

How large does n need to be to use clt

sophia

56:30

What’s considered a large n? Is there a cutoff value?

Stephen

56:58

yes 9ty1

Noah Wadhwani

01:00:09

bet

Alex Xi

01:01:33

Great lecture, thank you professor

YeJin Ahn

01:01:35

Thank you!

Laura Nguyen

01:01:36

thanks

Brendan Co

01:01:37

thanks

Jingyu Han

01:01:37

thank you!

chelsie

01:01:39

thank uu

Joshua

01:01:39

Thanks!

mayareuven

01:01:39

Thanks!

louisnorris

01:01:40

Thank you!

Sophie Liu

01:01:40

thanks!

Dayne Tran

01:01:46

Thanks!

sophia

01:02:13

Would you please explain discrete vs. continuous again?

lauraherron

01:10:01

thank you professor!