Pharm D

11-20-2006, 07:08 PM

Good luck!:grad:

View Full Version : more questions- anyone knows the answer?

Pharm D

11-20-2006, 07:08 PM

Good luck!:grad:

dussamkumar

11-20-2006, 07:19 PM

i got 97 , how much u got pharm d, infact i am also having the same doubts, i am about to keep in the forum, but i have seen yours.

all the best..

waiting for the answers from our friends

all the best..

waiting for the answers from our friends

fizzbizz

11-20-2006, 08:53 PM

1 b

2?

3c?

4c

5d

2?

3c?

4c

5d

dussamkumar

11-20-2006, 09:46 PM

hey fizzzbizz

where did u get this answers, let me know, and plz explain

where did u get this answers, let me know, and plz explain

fizzbizz

11-20-2006, 09:51 PM

i had posted an epi link ..the details are in there ..sorry cant recall it now as lost all old stuff...anyone who nows can u pls post the epi links here again

u can also chek these:

http://en.wikipedia.org/wiki/Study_design

http://en.wikipedia.org/wiki/Epidemiological_methods

u can also chek these:

http://en.wikipedia.org/wiki/Study_design

http://en.wikipedia.org/wiki/Epidemiological_methods

gigs

11-20-2006, 09:57 PM

hey i think the answer for question 4 should be d, which means that placebo is also showing effect in some percentage of population

correct me if i m wrong

correct me if i m wrong

Pharm D

11-20-2006, 10:20 PM

Good luck!:grad:

fizzbizz

11-20-2006, 10:41 PM

hey i think the answer for question 4 should be d, which means that placebo is also showing effect in some percentage of population

correct me if i m wrong

no its definitely not 4 bcos its talking abt null hypothesis and probability of 5 pc chance..i dunno how to explain sorry

correct me if i m wrong

no its definitely not 4 bcos its talking abt null hypothesis and probability of 5 pc chance..i dunno how to explain sorry

Pharm D

11-21-2006, 04:26 AM

Thanks.

Good luck!

Good luck!

mtvua

11-21-2006, 07:25 PM

if p<0.05 means that difference is real. try to read statistical significance. it's not easy.

fizzbizz

11-22-2006, 07:54 AM

P-Value

The probability value (p-value) of a statistical hypothesis test is the probability of getting a value of the test statistic as extreme as or more extreme than that observed by chance alone, if the null hypothesis H0, is true.

*********************

It is the probability of wrongly rejecting the null hypothesis if it is in fact true.

It is equal to the significance level of the test for which we would only just reject the null hypothesis. The p-value is compared with the significance level and, if it is smaller, the result is significant. That is, if the null hypothesis were to be rejected at

= 0.05, this would be reported as 'p < 0.05'.

Small p-values suggest that the null hypothesis is unlikely to be true. The smaller it is, the more convincing is the rejection of the null hypothesis. It indicates the strength of evidence for say, rejecting the null hypothesis H0, rather than simply concluding 'reject H0' or 'do not reject H0'.

Significance Level

The significance level of a statistical hypothesis test is a fixed probability of wrongly rejecting the null hypothesis H0, if it is in fact true.

*********************

It is the probability of a type I error (http://www.cas.lancs.ac.uk/glossary_v1.1/#1err) and is set by the investigator in relation to the consequences of such an error. That is, we want to make the significance level as small as possible in order to protect the null hypothesis and to prevent, as far as possible, the investigator from inadvertently making false claims.

The significance level is usually denoted by

Significance Level = P(type I error) =

Usually, the significance level is chosen to be = 0.05 = 5%.

The probability value (p-value) of a statistical hypothesis test is the probability of getting a value of the test statistic as extreme as or more extreme than that observed by chance alone, if the null hypothesis H0, is true.

*********************

It is the probability of wrongly rejecting the null hypothesis if it is in fact true.

It is equal to the significance level of the test for which we would only just reject the null hypothesis. The p-value is compared with the significance level and, if it is smaller, the result is significant. That is, if the null hypothesis were to be rejected at

= 0.05, this would be reported as 'p < 0.05'.

Small p-values suggest that the null hypothesis is unlikely to be true. The smaller it is, the more convincing is the rejection of the null hypothesis. It indicates the strength of evidence for say, rejecting the null hypothesis H0, rather than simply concluding 'reject H0' or 'do not reject H0'.

Significance Level

The significance level of a statistical hypothesis test is a fixed probability of wrongly rejecting the null hypothesis H0, if it is in fact true.

*********************

It is the probability of a type I error (http://www.cas.lancs.ac.uk/glossary_v1.1/#1err) and is set by the investigator in relation to the consequences of such an error. That is, we want to make the significance level as small as possible in order to protect the null hypothesis and to prevent, as far as possible, the investigator from inadvertently making false claims.

The significance level is usually denoted by

Significance Level = P(type I error) =

Usually, the significance level is chosen to be = 0.05 = 5%.

bva

11-22-2006, 07:58 AM

P-value and alpha is the same?

Thankssssssssss so much, Fizzbizz. Never know about this P-value before, I was thinking about p in binomial.

Thankssssssssss. [goodjob]

Thankssssssssss so much, Fizzbizz. Never know about this P-value before, I was thinking about p in binomial.

Thankssssssssss. [goodjob]

mpb

11-22-2006, 10:53 PM

where are the questions?, can someone PM me the questions... thanks

mtvua

11-22-2006, 11:11 PM

if the null hypothesis were to be rejected at

= 0.05, this would be reported as 'p < 0.05'.

Ho is that there is no difference b/w antihypertensive and placebo. so if null hypothesis is rejected then difference is real.

correct me if i am wrong.

= 0.05, this would be reported as 'p < 0.05'.

Ho is that there is no difference b/w antihypertensive and placebo. so if null hypothesis is rejected then difference is real.

correct me if i am wrong.

mtvua

11-23-2006, 03:10 PM

null hypothesis states that there is no difference in this case b/w hypertensive and placebo.

alternative hypotheses is that there is difference.

in this case 5 percent probability that there is no difference, i.e. Ho is correct, and 95 percent that it is incorrect, Ho should be rejected and Ha should be accepted( that there is difference)

conventionally statistitians decided that Ho should be rejected if probability is <.05. in this case probability that there is no difference between antihypertensive and placebo only 5 percent.

probability at which Ho should be rejected called significance level or alpha, conventionally it is .05 but can be .01.

type I error, alpha. it when you see smth that is not there, like convicting Innocent man( i remember type I - Innocent), when you see difference when it is not there. when there is difference you reject Ho and type I error when you reject it when in reality it is true.

type II error, beta. it when you don't see difference that is there. like not convicting guilty man. you don't see difference, you accept Ho but in reality it is not true.

i really hope i didn't confuse you more... correct me if i am wrong.

alternative hypotheses is that there is difference.

in this case 5 percent probability that there is no difference, i.e. Ho is correct, and 95 percent that it is incorrect, Ho should be rejected and Ha should be accepted( that there is difference)

conventionally statistitians decided that Ho should be rejected if probability is <.05. in this case probability that there is no difference between antihypertensive and placebo only 5 percent.

probability at which Ho should be rejected called significance level or alpha, conventionally it is .05 but can be .01.

type I error, alpha. it when you see smth that is not there, like convicting Innocent man( i remember type I - Innocent), when you see difference when it is not there. when there is difference you reject Ho and type I error when you reject it when in reality it is true.

type II error, beta. it when you don't see difference that is there. like not convicting guilty man. you don't see difference, you accept Ho but in reality it is not true.

i really hope i didn't confuse you more... correct me if i am wrong.

bva

11-23-2006, 04:34 PM

Still confused a bit, :doh:

Could you please clarify whether p-value and alpha is different or the same?

Thanksssssssssssssss so much.

null hypothesis states that there is no difference in this case b/w hypertensive and placebo.

alternative hypotheses is that there is difference.

in this case 5 percent probability that there is no difference, i.e. Ho is correct, and 95 percent that it is incorrect, Ho should be rejected and Ha should be accepted( that there is difference)

conventionally statistitians decided that Ho should be rejected if probability is <.05. in this case probability that there is no difference between antihypertensive and placebo only 5 percent.

probability at which Ho should be rejected called significance level or alpha, conventionally it is .05 but can be .01.

type I error, alpha. it when you see smth that is not there, like convicting Innocent man( i remember type I - Innocent), when you see difference when it is not there. when there is difference you reject Ho and type I error when you reject it when in reality it is true.

type II error, beta. it when you don't see difference that is there. like not convicting guilty man. you don't see difference, you accept Ho but in reality it is not true.

i really hope i didn't confuse you more... correct me if i am wrong.

Could you please clarify whether p-value and alpha is different or the same?

Thanksssssssssssssss so much.

null hypothesis states that there is no difference in this case b/w hypertensive and placebo.

alternative hypotheses is that there is difference.

in this case 5 percent probability that there is no difference, i.e. Ho is correct, and 95 percent that it is incorrect, Ho should be rejected and Ha should be accepted( that there is difference)

conventionally statistitians decided that Ho should be rejected if probability is <.05. in this case probability that there is no difference between antihypertensive and placebo only 5 percent.

probability at which Ho should be rejected called significance level or alpha, conventionally it is .05 but can be .01.

type I error, alpha. it when you see smth that is not there, like convicting Innocent man( i remember type I - Innocent), when you see difference when it is not there. when there is difference you reject Ho and type I error when you reject it when in reality it is true.

type II error, beta. it when you don't see difference that is there. like not convicting guilty man. you don't see difference, you accept Ho but in reality it is not true.

i really hope i didn't confuse you more... correct me if i am wrong.

mtvua

11-23-2006, 07:07 PM

as i understand it p is probability. alpha it is a point when the probability that there is no difference is .05 ( 5 percent). it is like a border. if probability is more than .05 (i.e. more than alpha) then Ho is accepted, when probability is less than .05 then it rejected.

let me know if you understand now.

correct me if i am wrong, i am still studying it. very confusing.

let me know if you understand now.

correct me if i am wrong, i am still studying it. very confusing.