ECMT quiz 2 (1 Viewer)

[stazi]

Confidence interval:

18.3% < u < 36%

That's what I got, but make sure that you use 18.3%, 36%
Murray said the textbook was wrong to use equal or less than signs.
However, murray = dick.

 

[Lainee]

3g)

ii) o^2(x+y) = o^2(x) + o^2(y) + 2cov(x, y)

Var(3x - 2y + 1) =

Var(3x) + Var (-2y) + 0 =

3^2(Var x) + -2^2Var(y) + 2cov(x, y)

Var(x) = 16^2 = 256
Var(y) = 4^2 = 16

Therefore,

3^2(256) + (-2)^2(16) - 20 = 2220

I think there's a slight problem with the formula you used:

Var(aX+bY)=a^2Var(X)+b^2Var(Y) + 2abCov(X,Y)

What you did was change the last term to 2Cov(X,Y) which would be okay if a=b=1, but in this case you must say 2abCov(X,Y).

The alternative answer:

3^2(256) + (-2)^2(16) + 2(3)(-2)(-10) = 2488

 

[sarevok]

oic

thanks

 

[stazi]

This quiz sucks. There's some good questions. Some difficult, but good questions nonetheless that you won't have a prob with if you study for.
Then there's a few that suck, such as interpreting results and stuff like that.

 

[04er]

when we have something like X~N(50,25) does that mean X~N(Mean,Variance) i.e. X~N(Mean,Std_Dev^2)?

 

[04er]

could someone please confirm this?

For question 2.b)

Assuming that X~N(Mean,Std_Dev^2)

and we're given X~N(50,5^2)

therefore Mean (u) = 50 and Std_Dev (o) = 5

As P(a<X<b) = 0.95 and a and b are equidistant from 50 (the mean),

P(X<a) = 0.025 and P(X>b) = 0.025

for X = a , Z = -1.96 (referring to the Normal Distribution table)

Z = (X - u) / o

i.e. -1.96 = (X - 50) / 5

Rearranging we get X = 40.2

but X = a

i.e. a = 40.2

therefore distance from mean, 50, = 9.8

and because a and b are equidistant from 50 (given), b = 50 + 9.8 = 59.8

is that right? sorry i'm extremely behind and i'm only just starting the quiz questions...

EDIT: Never mind, just realised absolution got the same answer. Thanks!
EDIT: Lainee got 1 and 99. Which answer is right!? I'm thinking 40.2 and 59.8 are the right ones because Lainee used Std_Dev as 25, which is contrary to the lecture notes... unless of course the lecture notes are now wrong

 

[04er]

when we have something like X~N(50,25) does that mean X~N(Mean,Variance) i.e. X~N(Mean,Std_Dev^2)?

I just confirmed that this is right from the lecture notes (wk 6).

EDIT: realised that too_lazy also confirmed this. I should really read all the pages before asking questions

 

[jpr333]

Yes yes you should, had the quiz today easy questions, think I'll get 10.

 

[ToO LaZy ^*]

Yes yes you should, had the quiz today easy questions, think I'll get 10.

what questions did you get?

 

[stazi]

i pooped up.
I thought it was N(mean,stdev)
Heeeaps of people made the same mistake

 

[ToO LaZy ^*]

what questions did you get?

.................

 

[stazi]

i got a Z>whatever Q1.
X~N(10,64) P(X<64) Q2
and cant remember what for Q3. Really simple one though. Just a normal find the z value of a sampling distribution Q.

 

[jpr333]

I had the equivalent of qs 1(c), 2(b) and 3(a)

 

[04er]

I had the equivalent of qs 1(c), 2(b) and 3(a)

i envy you...

 

[04er]

someone please help me with 3. g) iii) !!!!!!!! or at least refer me to a page... please

 

[jpr333]

When they are statistically independant covariance is 0.

 

[Lainee]

i got a Z>whatever Q1.
X~N(10,64) P(X<64) Q2
and cant remember what for Q3. Really simple one though. Just a normal find the z value of a sampling distribution Q.

I got the same questions for 1 and 2, and for 3 I got 3(d) with just some numbers changed. So glad... I just couldn't get those proportion formulas to stay in my head.

someone please help me with 3. g) iii) !!!!!!!! or at least refer me to a page... please

Go back to what the definition of covariance is (ref: pg 169-170 textbook). If X and Y are independent, covariance would be equal to zero because there is no relationship between discrete random variables X and Y (whatever happens to X, there is no effect on Y).

 

[04er]

Go back to what the definition of covariance is (ref: pg 169-170 textbook). If X and Y are independent, covariance would be equal to zero because there is no relationship between discrete random variables X and Y (whatever happens to X, there is no effect on Y).

Thank you for your help Lainee and jpr333 and Sarevok

Does anyone know how to do Q 2.d and 3 k) (where do we get the proof!?!?!)?? They're the only ones I have left... I would die if i got that tomorrow... I have no idea what formula we're meant to use

 

[Lainee]

2(d) is pretty straightforward use of the formula on page 237 of the textbook 'Finding Z for the sampling distribution of the mean'.

 

[04er]

2(d) is pretty straightforward use of the formula on page 237 of the textbook 'Finding Z for the sampling distribution of the mean'.

Lainee to the rescue... you're my hero! hehehe Do you know where to find the proof for 3k?