Comment author:Jeff_Kaufman
20 February 2016 06:08:47AM
*
3 points
[-]

it looks like you're using a one-sided t-test to get your p-value.

I agree that a two-sided test would be the right thing to use here, and p-value calculations aren't something I fully understand. Is this calculation one-sided or two-sided?

Comment author:Dan_Keys
20 February 2016 06:50:27AM
2 points
[-]

I can't tell what's being done in that calculation.

I'm getting a p-value of 0.108 from a Pearson chi-square test (with cell values 55, 809; 78, 856). A chi-square test and a two-tailed t-test should give very similar results with these data, so I agree with Michael that it looks like your p=0.053 comes from a one-tailed test.

## Comments (6)

Best*3 points [-]I agree that a two-sided test would be the right thing to use here, and p-value calculations aren't something I fully understand. Is this calculation one-sided or two-sided?

*4 points [-]It looks like the NORMDIST function on your sheet is taking the integral from 0 to

`z_score`

, which is one-sided. A two-sided test would takeI can't tell what's being done in that calculation.

I'm getting a p-value of 0.108 from a Pearson chi-square test (with cell values 55, 809; 78, 856). A chi-square test and a two-tailed t-test should give very similar results with these data, so I agree with Michael that it looks like your p=0.053 comes from a one-tailed test.

*1 point [-]Yes, you're right. Sorry! I redid it computationally and also got 0.108. Post updated.