Difference between revisions of "Student test"
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$$ | $$ | ||
− | t _ {n-} | + | t _ {n-1} = \sqrt n |
\frac{\overline{X}\; - a _ {0} }{s} | \frac{\overline{X}\; - a _ {0} }{s} | ||
, | , | ||
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\sum _ { i= 1} ^ { n } X _ {i} \ \textrm{ and } \ \ | \sum _ { i= 1} ^ { n } X _ {i} \ \textrm{ and } \ \ | ||
s ^ {2} = | s ^ {2} = | ||
− | \frac{1}{n-} | + | \frac{1}{n-1} |
− | + | \sum _ { i= 1} ^ { n } ( X _ {i} - \overline{X}\; ) ^ {2} | |
$$ | $$ | ||
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calculated with respect to the sample $ X _ {1} \dots X _ {n} $. | calculated with respect to the sample $ X _ {1} \dots X _ {n} $. | ||
When $ H _ {0} $ | When $ H _ {0} $ | ||
− | is correct, the statistic $ t _ {n-} | + | is correct, the statistic $ t _ {n-1} $ |
− | is subject to the [[ | + | is subject to the [[Student distribution]] with $ f = n- 1 $ |
degrees of freedom, i.e. | degrees of freedom, i.e. | ||
$$ | $$ | ||
− | {\mathsf P} \{ | t _ {n-} | + | {\mathsf P} \{ | t _ {n-1} | < t \mid H _ {0} \} = \ |
− | 2S _ {n-} | + | 2S _ {n-1} ( t) - 1,\ \ |
t > 0, | t > 0, | ||
$$ | $$ | ||
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\left | \sqrt n | \left | \sqrt n | ||
\frac{\overline{X}\; - a _ {0} }{s} | \frac{\overline{X}\; - a _ {0} }{s} | ||
− | \right | < t _ {n-} | + | \right | < t _ {n-1} \left ( 1 - |
\frac \alpha {2} | \frac \alpha {2} | ||
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$$ | $$ | ||
− | where $ t _ {n-} | + | where $ t _ {n-1} ( 1- \alpha /2) $ |
− | is the [[ | + | is the [[quantile]] of level $ 1- \alpha /2 $ |
of the Student distribution with $ f= n- 1 $ | of the Student distribution with $ f= n- 1 $ | ||
− | degrees of freedom, i.e. $ t _ {n-} | + | degrees of freedom, i.e. $ t _ {n-1} ( 1- \alpha /2) $ |
− | is the solution of the equation $ S _ {n-} | + | is the solution of the equation $ S _ {n-1} ( t) = 1- \alpha /2 $. |
On the other hand, if | On the other hand, if | ||
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\left | \sqrt n | \left | \sqrt n | ||
\frac{\overline{X}\; - a _ {0} }{s} | \frac{\overline{X}\; - a _ {0} }{s} | ||
− | \right | \geq t _ {n-} | + | \right | \geq t _ {n-1} \left ( 1 - |
\frac \alpha {2} | \frac \alpha {2} | ||
Line 135: | Line 135: | ||
$$ | $$ | ||
s _ {1} ^ {2} = | s _ {1} ^ {2} = | ||
− | \frac{1}{n-} | + | \frac{1}{n-1} |
− | + | \sum _ { i= 1} ^ { n } ( X _ {i} - \overline{X}\; ) ^ {2} | |
\ \textrm{ and } \ \ | \ \textrm{ and } \ \ | ||
s _ {2} ^ {2} = | s _ {2} ^ {2} = | ||
− | \frac{1}{m-} | + | \frac{1}{m-1} |
− | + | \sum _ { j= 1} ^ { m } ( Y _ {j} - \overline{Y}\; ) ^ {2} | |
$$ | $$ | ||
Latest revision as of 20:10, 10 January 2024
$ t $-
test
A significance test for the mean value of a normal distribution.
The single-sample Student test.
Let the independent random variables $ X _ {1} \dots X _ {n} $ be subject to the normal law $ N _ {1} ( a, \sigma ^ {2} ) $, the parameters $ a $ and $ \sigma ^ {2} $ of which are unknown, and let a simple hypothesis $ H _ {0} $: $ a = a _ {0} $ be tested against the composite alternative $ H _ {1} $: $ a \neq a _ {0} $. In solving this problem, a Student test is used, based on the statistic
$$ t _ {n-1} = \sqrt n \frac{\overline{X}\; - a _ {0} }{s} , $$
where
$$ \overline{X}\; = \frac{1}{n} \sum _ { i= 1} ^ { n } X _ {i} \ \textrm{ and } \ \ s ^ {2} = \frac{1}{n-1} \sum _ { i= 1} ^ { n } ( X _ {i} - \overline{X}\; ) ^ {2} $$
are estimators of the parameters $ a $ and $ \sigma ^ {2} $, calculated with respect to the sample $ X _ {1} \dots X _ {n} $. When $ H _ {0} $ is correct, the statistic $ t _ {n-1} $ is subject to the Student distribution with $ f = n- 1 $ degrees of freedom, i.e.
$$ {\mathsf P} \{ | t _ {n-1} | < t \mid H _ {0} \} = \ 2S _ {n-1} ( t) - 1,\ \ t > 0, $$
where $ S _ {f} ( t) $ is the Student distribution function with $ f $ degrees of freedom. According to the single-sample Student test with significance level $ \alpha $, $ 0 < \alpha < 0.5 $, the hypothesis $ H _ {0} $ must be accepted if
$$ \left | \sqrt n \frac{\overline{X}\; - a _ {0} }{s} \right | < t _ {n-1} \left ( 1 - \frac \alpha {2} \right ) , $$
where $ t _ {n-1} ( 1- \alpha /2) $ is the quantile of level $ 1- \alpha /2 $ of the Student distribution with $ f= n- 1 $ degrees of freedom, i.e. $ t _ {n-1} ( 1- \alpha /2) $ is the solution of the equation $ S _ {n-1} ( t) = 1- \alpha /2 $. On the other hand, if
$$ \left | \sqrt n \frac{\overline{X}\; - a _ {0} }{s} \right | \geq t _ {n-1} \left ( 1 - \frac \alpha {2} \right ) , $$
then, according to the Student test of level $ \alpha $, the tested hypothesis $ H _ {0} $: $ a = a _ {0} $ has to be rejected, and the alternative hypothesis $ H _ {1} $: $ a \neq a _ {0} $ has to be accepted.
The two-sample Student test.
Let $ X _ {1} \dots X _ {n} $ and $ Y _ {1} \dots Y _ {m} $ be mutually independent normally-distributed random variables with the same unknown variance $ \sigma ^ {2} $, and let
$$ {\mathsf E} X _ {1} = \dots = {\mathsf E} X _ {n} = a _ {1} , $$
$$ {\mathsf E} Y _ {1} = \dots = {\mathsf E} Y _ {m} = a _ {2} , $$
where the parameters $ a _ {1} $ and $ a _ {2} $ are also unknown (it is often said that there are two independent normal samples). Moreover, let the hypothesis $ H _ {0} $: $ a _ {1} = a _ {2} $ be tested against the alternative $ H _ {1} $: $ a _ {1} \neq a _ {2} $. In this instance, both hypotheses are composite. Using the observations $ X _ {1} \dots X _ {n} $ and $ Y _ {1} \dots Y _ {m} $ it is possible to calculate the estimators
$$ \overline{X}\; = \frac{1}{n} \sum _ { i=1 } ^ { n } X _ {i} \ \textrm{ and } \ \ \overline{Y}\; = \frac{1}{m} \sum _ { j= 1} ^ { m } Y _ {j} $$
for the unknown mathematical expectations $ a _ {1} $ and $ a _ {2} $, as well as the estimators
$$ s _ {1} ^ {2} = \frac{1}{n-1} \sum _ { i= 1} ^ { n } ( X _ {i} - \overline{X}\; ) ^ {2} \ \textrm{ and } \ \ s _ {2} ^ {2} = \frac{1}{m-1} \sum _ { j= 1} ^ { m } ( Y _ {j} - \overline{Y}\; ) ^ {2} $$
for the unknown variance $ \sigma ^ {2} $. Moreover, let
$$ s ^ {2} = \frac{1}{n+m- 2} [( n- 1) s _ {1} ^ {2} + ( m- 1) s _ {2} ^ {2} ]. $$
Then, when $ H _ {0} $ is correct, the statistic
$$ t _ {n+} m- 2 = \frac{\overline{X}\; - \overline{Y}\; }{s \sqrt 1/n+ 1/m } $$
is subject to the Student distribution with $ f = n+ m- 2 $ degrees of freedom. This fact forms the basis of the two-sample Student test for testing $ H _ {0} $ against $ H _ {1} $. According to the two-sample Student test of level $ \alpha $, $ 0 < \alpha < 0.5 $, the hypothesis $ H _ {0} $ is accepted if
$$ | t _ {n+ m- 2} | < t _ {n+m- 2} \left ( 1 - \frac \alpha {2} \right ) , $$
where $ t _ {n+m- 2} ( 1- \alpha /2) $ is the quantile of level $ 1- \alpha /2 $ of the Student distribution with $ f= n+ m- 2 $ degrees of freedom. If
$$ | t _ {n+} m- 2 | \geq t _ {n+m- 2} \left ( 1- \frac \alpha {2} \right ) , $$
then, according to the Student test of level $ \alpha $, the hypothesis $ H _ {0} $ is rejected in favour of $ H _ {1} $.
References
[1] | H. Cramér, "Mathematical methods of statistics" , Princeton Univ. Press (1946) |
[2] | S.S. Wilks, "Mathematical statistics" , Wiley (1962) |
[3] | N.V. Smirnov, I.V. Dunin-Barkovskii, "Mathematische Statistik in der Technik" , Deutsch. Verlag Wissenschaft. (1969) (Translated from Russian) |
[4] | L.N. Bol'shev, N.V. Smirnov, "Tables of mathematical statistics" , Libr. math. tables , 46 , Nauka (1983) (In Russian) (Processed by L.S. Bark and E.S. Kedrova) |
[5] | Yu.V. Linnik, "Methoden der kleinsten Quadraten in moderner Darstellung" , Deutsch. Verlag Wissenschaft. (1961) (Translated from Russian) |
Student test. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Student_test&oldid=54963