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Hypothesis Testing Using One-Sample t-Tests

Hypothesis Testing Using One-Sample t-Tests

By Mike Moffatt, About.com

Again using site Graphpad Quickcalcs: One sample t test we can quickly obtain the p-value for our second hypothesis test:

Steps Needed to Estimate a p-value for B2= -0.4

  • Click on the radio box containing “Enter mean, SEM and N.” Mean is the parameter value we estimated, SEM is the standard error, and N is the number of observations.
  • Enter -0.31 in the box labelled “Mean:”.
  • Enter 0.03 in the box labelled “SEM:”
  • Enter 219 in the box labelled “N:”, as this is the number of observations we had.
  • Under “3. Specify the hypothetical mean value” click on the radio button beside the blank box. In that box enter -0.4, as that is our hypothesis.
  • Click “Calculate Now”
You should get an output page. On the top of the output page you should see the following information:

    P value and statistical significance: The two-tailed P value equals 0.0030
    By conventional criteria, this difference is considered to be statistically significant.
So our p-value is 0.0030 which is less than 0.05. In this case we reject our null hypothesis and accept our alternative hypothesis. In other words, for this parameter, our theory did not match the data.

We used U.S. data to estimate the Okun's Law model. Using that data we found that both the intercept and slope parameters are statistically significantly different than those in Okun's Law. Therefore we can conclude that in the United States Okun's Law does not hold.

Now you've seen how to calculate and use one-sample t-tests, you will be able to interpret the numbers you've calculated in your regression.

If you'd like to ask a question about econometrics, hypothesis testing, or any other topic or comment on this story, please use the feedback form. If you're interested in winning cash for your economics term paper or article, be sure to check out "The 2004 Moffatt Prize in Economic Writing"

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