What do paired t tests show?

What do paired t tests show?

The paired sample t-test, sometimes called the dependent sample t-test, is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. In a paired sample t-test, each subject or entity is measured twice, resulting in pairs of observations.

What is the null hypothesis for a paired t-test?

The null hypothesis is that the mean difference between paired observations is zero. When the mean difference is zero, the means of the two groups must also be equal. Because of the paired design of the data, the null hypothesis of a paired t–test is usually expressed in terms of the mean difference.

What is the null hypothesis for a 2 sample t test?

The default null hypothesis for a 2-sample t-test is that the two groups are equal. You can see in the equation that when the two groups are equal, the difference (and the entire ratio) also equals zero.

How do you know if t statistic is significant?

As an example if your level of significance is 0.05, the correspondent t-stat value is 1.96, thus when the t-stat reported in the output is higher than 1.96 you reject the null hypothesis and your coefficient is significant at 5% significance level.

What is p-value in Stata?

The p-value is a matter of convenience for us. STATA automatically takes into account the number of degrees of freedom and tells us at what level our coefficient is significant. If it is significant at the 95% level, then we have P < 0.05. If it is significant at the 0.01 level, then P < 0.01.

What is a good t-statistic value?

Thus, the t-statistic measures how many standard errors the coefficient is away from zero. Generally, any t-value greater than +2 or less than – 2 is acceptable. The higher the t-value, the greater the confidence we have in the coefficient as a predictor.

What is the test command in Stata?

The test command, when applied to a single hypothesis, produces an F- statistic with one numerator d.f. The t-statistic of which you speak is the square root of that F-statistic. Its p-value is identical to that of the F-statistic. E.g. display tstat will then give you the tstat with sign.

What does prob F mean?

• Prob > F is the p-value for the whole model test. Since the Prob > F is less than than 0.05, reject the null hypothesis. Conclude that there are differences between at least two of the means.

What does PR t mean?

Pr(T < t), Pr(T > t) – These are the one-tailed p-values evaluating the null against the alternatives that the mean is less than 50 (left test) and greater than 50 (right test). These probabilities are computed using the t distribution. Again, if p-value is less than the pre-specified alpha level (usually .

What is the value of the F statistic reported by Stata?

f. F and Prob > F – The F-value is the Mean Square Model ( divided by the Mean Square Residual (, yielding F=46.69. The p-value associated with this F value is very small (0.0000).

How do I report F-test results?

The key points are as follows:

1. Set in parentheses.
2. Uppercase for F.
3. Lowercase for p.
4. Italics for F and p.
5. F-statistic rounded to three (maybe four) significant digits.
6. F-statistic followed by a comma, then a space.
7. Space on both sides of equal sign and both sides of less than sign.

What is considered a high F value?

The F ratio is the ratio of two mean square values. If the null hypothesis is true, you expect F to have a value close to 1.0 most of the time. A large F ratio means that the variation among group means is more than you’d expect to see by chance.

What does a high F value mean?

The F-Statistic: Variation Between Sample Means / Variation Within the Samples. The high F-value graph shows a case where the variability of group means is large relative to the within group variability. In order to reject the null hypothesis that the group means are equal, we need a high F-value.

How do you know if F value is significant?

If you get a large f value (one that is bigger than the F critical value found in a table), it means something is significant, while a small p value means all your results are significant. The F statistic just compares the joint effect of all the variables together.

How do you know if a regression model is significant?

If your regression model contains independent variables that are statistically significant, a reasonably high R-squared value makes sense. The statistical significance indicates that changes in the independent variables correlate with shifts in the dependent variable.