Descriptives - Here's an example of what a descriptives command produces - more than one variable at a time.

Notes
Output Created 15-AUG-2003 11:52:05
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used All non-missing data are used.
Syntax DESCRIPTIVES
VARIABLES=agemos malest femalest totalste
/STATISTICS=MEAN STDDEV MIN MAX .
Resources Elapsed Time 0:00:00.00

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation
age in months 36 38 67 51.69 8.532
male stereotype (0-12) 36 4 12 8.61 1.946
female stereotype (0-12) 36 2 12 7.78 3.006
stereotype total (m+f) 36 10 23 16.39 3.952
Valid N (listwise) 36




Crosstabs - this command will give you frequencies across more than one variable - and can calculate Chi-squares on the distribution.

Notes
Output Created 15-AUG-2003 12:02:24
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics for each table are based on all the cases with valid data in the specified range(s) for all variables in each table.
Syntax CROSSTABS
/TABLES=gender BY agegroup
/FORMAT= AVALUE TABLES
/STATISTIC=CHISQ
/CELLS= COUNT .
Resources Dimensions Requested 2
Cells Available 116508
Elapsed Time 0:00:00.00

Case Processing Summary

Cases
Valid Missing Total
N Percent N Percent N Percent
gender * agegroup 36 100.0% 0 .0% 36 100.0%


gender * agegroup Crosstabulation
Count

agegroup Total
younger (4-1 and down) older (4-2 and up)
gender male 9 12 21
female 8 7 15
Total 17 19 36

Chi-Square Tests

Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided)
Pearson Chi-Square .385(b) 1 .535

Continuity Correction(a) .080 1 .778

Likelihood Ratio .386 1 .535

Fisher's Exact Test


.736 .389
Linear-by-Linear Association .375 1 .541

N of Valid Cases 36



a Computed only for a 2x2 table
b 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.08.

NPar Tests

Notes
Output Created 15-AUG-2003 11:55:20
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics for each test are based on all cases with valid data for the variable(s) used in that test.
Syntax NPAR TEST
/CHISQUARE=agemos
/EXPECTED=EQUAL
/STATISTICS DESCRIPTIVES
/MISSING ANALYSIS.
Resources Number of Cases Allowed(a) 262144 cases
Elapsed Time 0:00:00.00
a Based on availability of special working memory.

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum
age in months 36 51.69 8.532 38 67

Chi-Square Test - You can not use this command to calculate a chi-square with 2 or more variables - only with one.

Frequencies

age in months

Observed N Expected N Residual
38 1 1.6 -.6
40 1 1.6 -.6
41 2 1.6 .4
43 2 1.6 .4
44 5 1.6 3.4
45 1 1.6 -.6
47 2 1.6 .4
48 2 1.6 .4
49 1 1.6 -.6
50 2 1.6 .4
51 1 1.6 -.6
52 1 1.6 -.6
53 1 1.6 -.6
54 1 1.6 -.6
57 1 1.6 -.6
58 2 1.6 .4
60 4 1.6 2.4
62 1 1.6 -.6
63 1 1.6 -.6
65 2 1.6 .4
66 1 1.6 -.6
67 1 1.6 -.6
Total 36


Test Statistics

age in months
Chi-Square(a) 14.111
df 21
Asymp. Sig. .865
a 22 cells (100.0%) have expected frequencies less than 5. The minimum expected cell frequency is 1.6.

T-Test - example of an independent samples t-test

Notes
Output Created 15-AUG-2003 12:00:33
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics for each analysis are based on the cases with no missing or out-of-range data for any variable in the analysis.
Syntax T-TEST
GROUPS=gender(0 1)
/MISSING=ANALYSIS
/VARIABLES=malest femalest totalste
/CRITERIA=CIN(.95) .
Resources Elapsed Time 0:00:01.00

Group Statistics

gender N Mean Std. Deviation Std. Error Mean
male stereotype (0-12) 0 21 8.86 1.459 .318
1 15 8.27 2.492 .643
female stereotype (0-12) 0 21 6.86 3.167 .691
1 15 9.07 2.282 .589
stereotype total (m+f) 0 21 15.71 4.002 .873
1 15 17.33 3.811 .984

Independent Samples Test

Levene's Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
Lower Upper
male stereotype (0-12) Equal variances assumed 9.324 .004 .895 34 .377 .59 .660 -.750 1.931
Equal variances not assumed

.823 20.821 .420 .59 .718 -.903 2.084
female stereotype (0-12) Equal variances assumed 2.666 .112 -2.304 34 .027 -2.21 .959 -4.158 -.261
Equal variances not assumed

-2.433 33.988 .020 -2.21 .908 -4.055 -.364
stereotype total (m+f) Equal variances assumed .985 .328 -1.220 34 .231 -1.62 1.327 -4.315 1.077
Equal variances not assumed

-1.231 31.193 .228 -1.62 1.316 -4.302 1.063

T-Test - example of a paired samples t-test

Notes
Output Created 15-AUG-2003 12:03:52
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics for each analysis are based on the cases with no missing or out-of-range data for any variable in the analysis.
Syntax T-TEST
PAIRS= malest WITH femalest (PAIRED)
/CRITERIA=CIN(.95)
/MISSING=ANALYSIS.
Resources Elapsed Time 0:00:00.00

Paired Samples Statistics

Mean N Std. Deviation Std. Error Mean
Pair 1 male stereotype (0-12) 8.61 36 1.946 .324
female stereotype (0-12) 7.78 36 3.006 .501

Paired Samples Correlations

N Correlation Sig.
Pair 1 male stereotype (0-12) & female stereotype (0-12) 36 .239 .161







Paired Samples Test

Paired Differences t df Sig. (2-tailed)
Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference
Lower Upper
Pair 1 male stereotype (0-12) - female stereotype (0-12) .83 3.167 .528 -.24 1.90 1.579 35 .123

Univariate Analysis of Variance - example of Univariate - 2 x 2 ANOVA

Notes
Output Created 15-AUG-2003 12:05:42
Comments
Input Data iJenn:Users:jenniferb:Desktop:SPSS Stuff:Gender Data.sav
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data File 36
Missing Value Handling Definition of Missing User-defined missing values are treated as missing.
Cases Used Statistics are based on all cases with valid data for all variables in the model.
Syntax UNIANOVA
totcorr BY gender agegroup
/METHOD = SSTYPE(3)
/INTERCEPT = INCLUDE
/PRINT = DESCRIPTIVE
/CRITERIA = ALPHA(.05)
/DESIGN = gender agegroup gender*agegroup .
Resources Elapsed Time 0:00:01.00

Between-Subjects Factors

Value Label N
gender 0 male 21
1 female 15
agegroup 1 younger (4-1 and down) 17
2 older (4-2 and up) 19

Descriptive Statistics
Dependent Variable: tot # of correct memory items
gender agegroup Mean Std. Deviation N
male younger (4-1 and down) 10.78 2.682 9
older (4-2 and up) 16.08 2.610 12
Total 13.81 3.723 21
female younger (4-1 and down) 10.75 4.833 8
older (4-2 and up) 15.00 4.163 7
Total 12.73 4.891 15
Total younger (4-1 and down) 10.76 3.717 17
older (4-2 and up) 15.68 3.198 19
Total 13.36 4.217 36

Tests of Between-Subjects Effects
Dependent Variable: tot # of correct memory items
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 222.333(a) 3 74.111 5.929 .002
Intercept 5987.280 1 5987.280 479.016 .000
GENDER 2.670 1 2.670 .214 .647
AGEGROUP 197.509 1 197.509 15.802 .000
GENDER * AGEGROUP 2.410 1 2.410 .193 .664
Error 399.972 32 12.499

Total 7049.000 36


Corrected Total 622.306 35


a R Squared = .357 (Adjusted R Squared = .297)