stat 226 gurus...

[baller1]

Can anyone help me with this??

2. CEO pay. A study of the pay of corporate chief executive ocers (CEOs) examined the increase in cash compensation of the CEOs of 104 companies, adjusted for inflation, in a recent year. The mean increase in real compensation was x = 6.9 percent and the standard deviation of the increases was s = 55 percent. Is this good evidence that the mean real compensation of all CEOs increased that year? To answer this question conduct a hypothesis test of the above situation using a signicance level of = 0.05:
(a) State the null and the alternative hypothesis.

H0 :

HA :

(b) Calculate the value of the test statistic.

test-statistic =

[mike4cy]

Can anyone help me with this??

2. CEO pay. A study of the pay of corporate chief executive ocers (CEOs) examined the increase in cash compensation of the CEOs of 104 companies, adjusted for ination, in a recent year. The mean increase in real compensation was x = 6.9 percent and the standard deviation of the increases was s = 55 percent. Is this good evidence that the mean real compensation of all CEOs increased that year? To answer this question conduct a hypothesis test of the above situation using a signicance level of = 0.05:
(a) State the null and the alternative hypothesis.

H0 :

HA :

(b) Calculate the value of the test statistic.

test-statistic =

It is equal to the squareroot of thank God I never have to do another Stats problem + if you think that is fun just wait until you get to 326

[isukendall]

You sure the SD isn't 5.5%?

[iahawkhunter]

It is equal to the squareroot of thank God I never have to do another Stats problem + if you think that is fun just wait until you get to 326

Reminds me of something my major professor told me: "A statistician's favorite dataset is 3 points. He can find a mean, median, mode, variance/standard deviation, fit a curve, and throw away 2 outliers."

[baller1]

You sure the SD isn't 5.5%?

Yeah, it says s=55% and x-hat = 6.9%. I don't understand how I am suppose to do the equation with the information given.

[CysRage]

I took this in Junior year of high school (dual credit). They told me it probably wouldn't transfer to Iowa State but I needed a class anyways so I took it. Lucky me that it transferred as Stat 226! I am now a junior in college and I cannot remember any of this or otherwise I would help you. Sorry!

[Cyclophile1]

Can anyone help me with this??

2. CEO pay. A study of the pay of corporate chief executive ocers (CEOs) examined the increase in cash compensation of the CEOs of 104 companies, adjusted for inflation, in a recent year. The mean increase in real compensation was x = 6.9 percent and the standard deviation of the increases was s = 55 percent. Is this good evidence that the mean real compensation of all CEOs increased that year? To answer this question conduct a hypothesis test of the above situation using a signicance level of = 0.05:
(a) State the null and the alternative hypothesis.

H0 :

HA :

(b) Calculate the value of the test statistic.

test-statistic =

Here's a big hint: It's the same 104 CEOs, so you are doing a repeated measures difference test.

[optimuslott]

This is not a repeated measures test as you are only assessing 104 ceo's once. Repeated measures would be assessing ceo's twice. So.....Here is what we have:

n=104
x-bar (mean) = 6.9%
sd = 55%

What we need is a classic z-test.

First, we need the standard error. Take 55% divided by the square root of 104. You should get a value of 5.393. Hold onto this information.

Second, the equation X-bar - mu divided by the standard error will give you a z-statistic (or your test statistic). In this case, mu = 0 (or we presume it to be equal to 0 as we do not know a population level mean). Thus, that leaves taking 6.9% divided by 5.393 (or the standard error). The end result is a test-statistic equal to 1.28 thus far below the critical value of 1.86 for a two-tail and 1.66 for a one tail. Thus, it is not significant at the .05 level for a one-tail directional hypothesis (such as an increase).

H0: The mean real compensation didn't increase or remained 0 (null)
Ha: The mean real compensation doesn't equal 0 and significantly increased.

enjoy and i may be wrong.

[baller1]

This is not a repeated measures test as you are only assessing 104 ceo's once. Repeated measures would be assessing ceo's twice. So.....Here is what we have:

n=104
x-bar (mean) = 6.9%
sd = 55%

What we need is a classic z-test.

First, we need the standard error. Take 55% divided by the square root of 104. You should get a value of 5.393. Hold onto this information.

Second, the equation X-bar - mu divided by the standard error will give you a z-statistic (or your test statistic). In this case, mu = 0 (or we presume it to be equal to 0 as we do not know a population level mean). Thus, that leaves taking 6.9% divided by 5.393 (or the standard error). The end result is a test-statistic equal to 1.28 thus far below the critical value of 1.86 for a two-tail and 1.66 for a one tail. Thus, it is not significant at the .05 level for a one-tail directional hypothesis (such as an increase).

H0: The mean real compensation didn't increase or remained 0 (null)
Ha: The mean real compensation doesn't equal 0 and significantly increased.

enjoy and i may be wrong.

Thank you! It looks good to me I appreciate the help.

[mike4cy]

This is not a repeated measures test as you are only assessing 104 ceo's once. Repeated measures would be assessing ceo's twice. So.....Here is what we have:

n=104
x-bar (mean) = 6.9%
sd = 55%

What we need is a classic z-test.

First, we need the standard error. Take 55% divided by the square root of 104. You should get a value of 5.393. Hold onto this information.

Second, the equation X-bar - mu divided by the standard error will give you a z-statistic (or your test statistic). In this case, mu = 0 (or we presume it to be equal to 0 as we do not know a population level mean). Thus, that leaves taking 6.9% divided by 5.393 (or the standard error). The end result is a test-statistic equal to 1.28 thus far below the critical value of 1.86 for a two-tail and 1.66 for a one tail. Thus, it is not significant at the .05 level for a one-tail directional hypothesis (such as an increase).

H0: The mean real compensation didn't increase or remained 0 (null)
Ha: The mean real compensation doesn't equal 0 and significantly increased.

enjoy and i may be wrong.

Crap, you beat me to it. I was just about to type that all into my keyboard

[azepp]

OMG my eyeballs are bleeding.