Path: janda.org/c10 > Overview of SPSS > Analyze > T-Test
Statistical Package for the Social Sciences

Syntax for T-TEST Command
T-Test
Use the T-TEST procedure to test for a statistically significant difference in means between two groups. The T-TEST computes a t-value which is a standardized score, similar to a z-score.

The t-value is calculated by dividing the difference in means between the groups by the standard error of the sampling difference between means. Remember that the "standard error" of a statistic (the statistic here is the value of the difference between the means) is just another name for the standard deviation of the sampling distribution for that statistic. The syntax for the most common T-TEST command is as follows:

T-TEST

The "groupvar" is the name of the variable used to create the two groups being compared. For example, "Region" might be the variable that furnishes the groups.

(n1,n2) indicates the two values of the groups being compared. To compare European nations with African nations in the POLITY dataset, specify (2,6).

variable is the name of the variable to analyze for difference of means. Suppose that you wanted to compare European nations with African nations for the percent of land under cultivation. The name of the variable in the POLITY data would be landcult.

 ```REGION seven world regions (POLITY dataset) Valid Cum Value Label Value Frequency Percent Percent Percent ANGLO-AMERICAN 1 5 4.5 4.5 4.5 EUROPEAN 2 17 15.3 15.3 19.8 LATIN AMERICAN 3 23 20.7 20.7 40.5 ASIA 4 15 13.5 13.5 54.1 MIDDLE EAST 5 11 9.9 9.9 64.0 AFRICA 6 32 28.8 28.8 92.8 EASTERN EUROPE 7 8 7.2 7.2 100.0 ----- ------ ------ Total 111 100.0 100.0 ```

GROUPS =
groupvar
(n1,n2) /
VARIABLES =
variable

T-TEST output

2 t-test groups= region (2,6) variables=landcult.

 t-tests for Independent Samples of REGION seven world regions Variable Number of Cases Mean SD SE of Mean LANDCULT % OF LAND UNDER ACTUAL CULTIVATION EUROPE 16 29.0000 17.588 4.397 AFRICA 31 11.1065 10.988 1.974 Mean Difference = 17.8935 Levene's Test for Equality of Variances: F= 5.620 P= .022 t-test for Equality of Means 95% Variances t-value df 2-Tail Sig. SE of Diff CI for Diff Equal 4.29 45 .000 4.171 (9.493, 26.295)

df 2-Tail Sig

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. . 45 .000

Unequal . 3.71 . 21.22 .001 4.820 (7.877, 27.910)

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