Math Is Fun Forum

http://imageshack.us/photo/my-images/3/19637915.png/

Hi guys,

My last question before crunch time, if you guys may. This one is a bit long (sorry)

a)  I have found k = 6/13 after using the property that a density function should equal 1

b)   In finding the CDF, I integrate each term in the piecewise function and solved for the constant as follows:

I solved for them and for A= 9/13 and B = 9/13. Is this correct?

For the CDF I'll obtain
0 for x<-1

for -1<x<0

fpr 0<x<1
0 for x>1

c)   In trying to obtain the mean I integrate

But I am obtaining a negative mean?

d) I can complete this myself if I get the mean correct

e) To find the probability X>0 Ive used

http://imageshack.us/photo/my-images/688/68986489.png/

Hi guys,

Please ignore part a)
Sorry for the stream of questions, I'm completing a past paper that does not have answers - so trying the bets I can

With part b) may I confirm if my work is correct:

I've decided to take the complement (1 - sample of 3 having no defective items)

I calculated this as

If this is correct, what would be the method using binomial probability?

Thanks
Lin

Hi guys,

I have a dilemma about a log-transformed regression

And so the transformation is

Assuming I have found the coefficient parameters for

and

, I am required to test the hypothesis that

by building the 95% confidence interval using

and

.

I am unsure about transforming back or keeping the interval. Here is my thinking

1) I use the standard errors of the coefficients of

and

from the regression output and build a confidence interval:

where t - is the critical value

2) Take the exponential to get back to normal scale and if the confidence interval contains 1, then accept the null hypothesis

Would this be the correct procedure?
Some people have said to me that this distorts the standard errors of the coefficient.
I would also like to note that the original data (pre-transformed) has no scale and was just raw numbers

Thanks in advance for any feedback,

Linda