Difference between test statistics and t-statistics?

J

Jones473

New member
Joined
Jun 18, 2026
Messages
0
Reaction score
0
In on of the practice tests on the CFA site you have to calculate the test statistic. The standard error is unknown, but the t-statistics is given as 4,28 and the coeffisient as 1,0264.
Exercise: “Based on the results in Exhibit 1, the value of the test statistic relating to Hamilton’s null hypothesis about the value of the coefficient on SPREAD is closest to:
Answer:
The null hypothesis is H0: bspread = 1.
The calculated value of the t-statistic is t = (1.0264 – 1.0)/standard error.
The standard error is 1.0264/4.28 = 0.24.
The calculated value for t = (1.0264 – 1.0)/0.24 = 0.11.
What is the difference between the t-statistics (which is given in the exercise) and the test-statistics calculated as 0,11?
 
Just to start– a test statistic is a standardized value calculated based on a sample and hypothesis. Some examples: f, t, z, chi-square, and others are all types of test statistics.
In this problem, though, they are asking specifically about a t-test. Generally, a given regression output has t-statistics calculated. These values are calculated assuming that bi = 0. If you want to test a different hypothesis, i.e. bi=1, you need to calculate that yourself. This problem is an example of that case. The t-stat of 4,28 is for the test of hypothesis that the coefficient = 0. The t-stat of 0,11 is for the test of hypothesis where the coefficient =1.
Hopefully, the difference is more clear.
 
Ok thanks a lot. So any t-stat from a regression output is always assuming that H0 –> Bi = 0?
 
You must log in or register to reply here.
Back
Top