The t-test gives the probability that the difference between the two means is caused by chance it is customary to say that if this probability is less than 005, that the difference is 'significant', the difference is not caused by chance. But there was no significant difference in midlife health for those with teen births compared to those who waited until they were age 20 to 24 there was no significant difference between 863,000 results on the web. The two-sample t-test is one of the most commonly used hypothesis tests in six sigma work it is applied to compare whether the average difference between two groups is really significant or if it is due instead to random chance it helps to answer questions like whether the average success rate is. Independent t-test for two samples introduction the independent t-test, also called the two sample t-test, independent-samples t-test or student's t-test, is an inferential statistical test that determines whether there is a statistically significant difference between the means in two unrelated groups.
If the p-value is less than 005, we reject the null hypothesis that there's no difference between the means and conclude that a significant difference does exist if the p-value is larger than 005, we cannot conclude that a significant difference exists. There is a statistically significant difference between the groups, even though the confidence intervals overlap  unfortunately, many scientists skip hypothesis tests and simply glance at plots to see if confidence intervals overlap. For example, question is is there a significant (not due to chance) difference in blood pressures between groups a and b if we give group a the test drug and group b a sugar pill and alternative hypothesis is there is a difference in blood pressures between groups a and b if we give group a the test drug and group b a sugar pill.
There is no significant difference in strength between superman and the average person the one-tailed probability is exactly half the value of the two-tailed probability there is a raging controversy (for about the last hundred years) on whether or not it is ever appropriate to use a one-tailed test. Statistics calculator will compare two percentages to determine whether there is a statistically significant difference between them it will also calculate confidence intervals around a percent. Significant difference a significant difference between two groups or two points in time means that there is a measurable difference between the groups and that, statistically, the probability of obtaining that difference by chance is very small (usually less than 5%.
In contrast the high significance level for type of vehicle (001 or 999%) indicates there is almost certainly a true difference in purchases of brand x by owners of different vehicles in the population from which the sample was drawn. Because post hoc tests are run to confirm where the differences occurred between groups, they should only be run when you have a shown an overall statistically significant difference in group means (ie, a statistically significant one-way anova result. Matched with an individual in the other sample the matching is done so that the two individuals are equivalent (or nearly equivalent) with respect to a specific variable that the researcher would like to control. There is also a difference between statistical significance and practical significance a study that is found to be statistically significant may not necessarily be practically significant a study that is found to be statistically significant may not necessarily be practically significant.
This page will calculate the z-ratio for the significance of the difference between two independent proportions, p a and p bfor the notation used here, n a and n b represent the total numbers of observations in two independent samples, a and b k a and k b represent the numbers of observations within each sample that are of particular interest and p a and p b represent the proportions k a /n. In order to test whether there is a difference between population means, we are going to make three assumptions: the two populations have the same variance this assumption is called the assumption of homogeneity of variance.
Read the table to determine if there is a statistically significant (greater than random chance) difference between the two percentages given the sizes of the samples significant differences when comparing percentages. In principle, a statistically significant result (usually a difference) is a result that's not attributed to chance more technically, it means that if the null hypothesis is true (which means there really is no difference), there's a low probability of getting a result that large or larger. Is the difference between the means of two samples different (significant) enough to say that some other characteristic (teaching method, teacher, gender, etc) could have caused it to conduct a t-test using an online calculator, complete the following steps.