http://www.ck12.org Chapter 8. Hypothesis Testing
TABLE8.3:
DF Probability
of Exceeding
the Critical
Value
0. 10 0. 05 0. 025 0. 01 0. 005 0. 001
1 3. 078 6. 314 12. 706 31. 821 63. 657 318. 313
2 1. 886 2. 920 4. 303 6. 965 9. 925 22. 327
3 1. 638 2. 353 3. 182 4. 541 5. 841 10. 215
4 1. 533 2. 132 2. 776 3. 747 4. 604 7. 173
5 1. 476 2. 015 2. 571 3. 365 4. 032 5. 893
6 1. 440 1. 943 2. 447 3. 143 3. 707 5. 208
7 1. 415 1. 895 2. 365 2. 998 3. 499 4. 782
8 1. 397 1. 860 2. 306 2. 896 3. 355 4. 499
9 1. 383 1. 833 2. 262 2. 821 3. 250 4. 296
10 1. 372 1. 812 2. 228 2. 764 3. 169 4. 143As the number of observations gets larger, thet-distribution approaches the shape of the normal distribution. In
general, once the sample size is large enough - usually about 120 - we would use the normal distribution or the
z-table instead.
In calculating thet-test statistic, we use the formula:
t=X ̄−μ
sx ̄where:
t=test statistic
X ̄=sample mean
μ=hypothesized population mean
sx ̄=estimated standard error
To estimate the standard error(sx ̄, we use the formulas/
√
nwheresis the standard deviation of the sample andnis
the sample size.
Example:
The high school athletic director is asked if football players are doing as well academically as the other student
athletes. We know from a previous study that the average GPA for the student athletes is 3.10 and that the standard
deviation of the sample is 0.54. After an initiative to help improve the GPA of student athletes, the athletic
director samples 20 football players and finds that their GPA is 3. 18 .Is there a significant improvement? Use a
.05 significance level.
Solution:
First, we establish our null and alternative hypotheses.
H 0 :μ= 3. 10
Ha:μ 6 = 3. 10