03
Oct
Two Tailed Test Statistics. How do you interpret a two tailed t test. The black-shaded areas of the distributions in the figure are the tails. A two-tailed test also known as a non directional hypothesis is the standard test of significance to determine if there is a relationship between variables in either direction. A test of a statistical hypothesis where the region of rejection is on both sides of the sampling distribution is called a two-tailed test.
In the field of research and experiments it pays to know the difference between one-tailed and two-tailed test as they are quite. μ 3 versus H A. The exact form of the test statistic is also important in determining the decision rule. Z-value x-bar μ σ n where x-bar average of the sample 105. The alternative hypothesis would be that the mean is less than 10 or greater than 10. For a two-tailed test we need to check if the test statistic TS is smaller than the negative critical value -CV or bigger than the positive critical value CV.
The mean is considered significantly different from x if the test statistic is in the top 25 or bottom 25 of its probability distribution resulting in a p-value less than 005.
A one-tailed test looks for an increase or decrease in the parameter whereas a two-tailed test looks for any change in the parameter which can be any change- increase or decrease. The black-shaded areas of the distributions in the figure are the tails. For example suppose the null hypothesis states that the mean is equal to 10. This means that we are going to find the z-value for the sample. We can perform the test at any level usually 1 5 or 10. N sample size 75.