1. ## basic statistics question

The question is,

Find the appropriate values for #'s.
a) P(Z<#)=.9
b) P(|Z|<#)=.9

I have no idea where to go with this or what i even have to do. Any help?

2. Originally Posted by yopy
The question is,

Find the appropriate values for #'s.
a) P(Z<#)=.9
b) P(|Z|<#)=.9

I have no idea where to go with this or what i even have to do. Any help?
Do you have a calculator like the TI 83 or 89 at your disposal? Or are you using a table of values

For the first one, you have to look in the table for the value .10000 as the tables give the probability that z># and you want <
Then you read off the z value from the side and add it to the number on the top to get your #

For the second you do the same things, but this time you are looking for .05 in the table because the absolute value means you want the same area in both tales, namely .05 in each tail (.05+.05=.1) since then if z is in between the tails it encompasses 90% of the area

The calculator's have normal inverse functions (the 89 does anyway I'm not positive about the 83)

3. well, i have a calculator, but i also have a z table in the back of my book. But i dont know if this question is supposed to be related to the z table, we covered that topic a while back and are learning new stuff at the moment, but then again your guess is as best as mine, anyways,

my z value for a would be -1.28, which is .1003 ( there is not .1000 value)

then for the second part, the table shows .5199 which correpsonds to .05

these are values coming from standard normal cumulative probabilities

does this sound right?

4. Originally Posted by yopy
well, i have a calculator, but i also have a z table in the back of my book. But i dont know if this question is supposed to be related to the z table, we covered that topic a while back and are learning new stuff at the moment, but then again your guess is as best as mine, anyways,

my z value for a would be -1.28, which is .1003 ( there is not .1000 value)

then for the second part, the table shows .5199 which correpsonds to .05

these are values coming from standard normal cumulative probabilities

does this sound right?
For the first part, you are correct there is no exact .10000, but your answer of -1.28 is definitely close enough, my calc gives me -1.28155 but you can't get that from the table

For the second part, you made an error somewhere. In my book, .0505 corresponds to 1.64 and .0495 corresponds to 1.65 so it's common practice to split the difference and call it 1.645