Descriptive Analysis:

Data Set

Procedural Steps

[Analyze] [Descriptive Statistics][Frequencies]

Transfer over variables of interest

[Statistics]  [Mean]; [S.E. (Standard Error)]; or whatever descriptive stats you need [Continue]

[Charts] [None]; [Bar Charts]; [Pie Charts]; [Histogram]  [OK]

Output

Statistics
Age / Gender / Before_exp_BP / After_exp_BP
N / Valid / 50 / 50 / 50 / 50
Missing / 0 / 0 / 0 / 0
Mean / 61.48 / 98.3020 / 88.5980
Std. Error of Mean / .920 / .73082 / .64507

Compute New Variables

Data Set

Procedural Steps

[Transform]  [Compute Variable]

Type Name of New Variable in “Target Variable”

Transfer First Variable, Click on function, Transfer Second Variable

Optional: [Type&Label]  Enter in label for new variable for future reference

[OK]

New Data Set

Independent T-Test (2 Tail)

Data Set

Procedural Steps

[Analyze]  [Compare Means]  [Independent-Samples T-Test]

Transfer Grouping Variable (Variable used to create 2 groups)  [Define Groups] (Enter labels for groups), Transfer Test Variables (Can be more than one if doing multiple T-tests

Optional: [Options]  change confidence interval

[OK]

Output

Group Statistics
Treatment / N / Mean / Std. Deviation / Std. Error Mean
After-Before / Control / 22 / -4.9455 / 2.25044 / .47980
Newdrug / 28 / -13.4429 / 5.73091 / 1.08304
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
After-Before / Equal variances assumed / 11.357 / .001 / 6.557 / 48 / .000 / 8.49740 / 1.29591 / 5.89180 / 11.10301
Equal variances not assumed / 7.173 / 36.815 / .000 / 8.49740 / 1.18456 / 6.09685 / 10.89795

Linear Regression-Statistics & Plots

Data Set

Procedural Steps

[Analyze]  [Regression]  [Linear]

Transfer Dependent Variable to “Dependent”, Transfer Independent Variable(s) to “Independent(s)”

[Statistics]  [Collinearity Diagnostics]  [Continue]

[Plots]  [Histogram] [Normal Probability Plot] & Transfer *ZRESID to “Y”, Transfer *ZPRED to “X”  [Continue]

[Continue]

Output

ANOVAa
Model / Sum of Squares / df / Mean Square / F / Sig.
1 / Regression / 478.830 / 3 / 159.610 / 4263.256 / .000b
Residual / .599 / 16 / .037
Total / 479.429 / 19
a. Dependent Variable: Amount of body fat
b. Predictors: (Constant), Midarm circumference, Thigh circumference, Triceps skinfold thickness

* Make sure the scatterplot has no visible trends*

Coefficientsa
Model / Unstandardized Coefficients / Standardized Coefficients / t / Sig. / Collinearity Statistics
B / Std. Error / Beta / Tolerance / VIF
1 / (Constant) / -32.327 / .713 / -45.348 / .000
Triceps skinfold thickness / .833 / .018 / .868 / 46.833 / .000 / .227 / 4.400
Thigh circumference / .524 / .012 / .380 / 42.459 / .000 / .973 / 1.028
Midarm circumference / .026 / .018 / .027 / 1.437 / .170 / .224 / 4.459
a. Dependent Variable: Amount of body fat

Linear Regression-Stepwise

Data Set

Procedural Steps

[Analyze]  [Regression]  [Linear]  Change “Enter” to “Stepwise”

Transfer Dependent Variable to “Dependent”, Transfer Independent Variable(s) to “Independent(s)”

[Statistics]  [Collinearity Diagnostics]  [Continue]

[Save]  [Standardized] in Residuals column  [Continue]

[Continue]

Outputs

Correlation

Data Set

Procedural Steps

[Analyze]  [Correlation]  [Bivariate]

Transfer all variables of interest to “Variables” (Correlations will be found between all variables listed)

Optional: [Options]  [Means and Standard Deviations]

Optional: Click on “Correlation Coefficients” to change or add statistical values and “Test of Significance” to change to one-tail or two-tail

[Continue]

Outputs:

Descriptive Statistics
Mean / Std. Deviation / N
Amount of body fat / 25.305 / 5.0233 / 20
Triceps skinfold thickness / 51.170 / 5.2346 / 20
Thigh circumference / 27.620 / 3.6471 / 20
Midarm circumference / 20.195 / 5.1062 / 20
Correlations
Amount of body fat / Triceps skinfold thickness / Thigh circumference / Midarm circumference
Amount of body fat / Pearson Correlation / 1 / .924** / .458* / .843**
Sig. (2-tailed) / .000 / .042 / .000
N / 20 / 20 / 20 / 20
Triceps skinfold thickness / Pearson Correlation / .924** / 1 / .085 / .878**
Sig. (2-tailed) / .000 / .723 / .000
N / 20 / 20 / 20 / 20
Thigh circumference / Pearson Correlation / .458* / .085 / 1 / .142
Sig. (2-tailed) / .042 / .723 / .549
N / 20 / 20 / 20 / 20
Midarm circumference / Pearson Correlation / .843** / .878** / .142 / 1
Sig. (2-tailed) / .000 / .000 / .549
N / 20 / 20 / 20 / 20
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

One Way ANOVAData used from BIOL 354 Fall 2014

Data Set

Procedural Steps

[Analyze]  [Compare Means]  [One-Way ANOVA]

Transfer Independent Variable into “Factor:” and the Dependent Variable into “Dependent List:”

[Post Hoc]  [Tukey’s]

[Continue]

Output

Measurement
TukeyHSDa
SubjCondtion / N / Subset for alpha = 0.05
1 / 2
Female5 / 8 / .01146
FemaleZero / 8 / .03867
Female15 / 8 / .33711
Female50 / 8 / .36717
MaleZero / 8 / .84473
Sig. / .174 / 1.000
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 8.000.
ANOVA
Measurement
Sum of Squares / df / Mean Square / F / Sig.
Between Groups / 3.618 / 4 / .904 / 9.321 / .000
Within Groups / 3.396 / 35 / .097
Total / 7.014 / 39

Two Way ANOVA

Data Set

Procedural Steps

[Analyze]  [General Linear Model]  [Univariate]

Transfer the Independent Variables to “Fixed Factors:” and the Dependent Variable to “Dependent Variable:”

[Plots]  Enter one variable into “Horizontal Axis” (this will be on the x-axis) and one variable into “Separate Lines”

If an independent variable has more than 2 levels: [Post Hoc]  Transfer Variables with 3 or more levels to “Post Hoc Tests for”  [Tukey’s]

[Continue]

Output

Tests of Between-Subjects Effects
Dependent Variable: Sales
Source / Type III Sum of Squares / df / Mean Square / F / Sig.
Corrected Model / 503.754a / 5 / 100.751 / 5.397 / .007
Intercept / 6740.928 / 1 / 6740.928 / 361.121 / .000
Shelf / 457.568 / 2 / 228.784 / 12.256 / .001
Store / 7.014 / 1 / 7.014 / .376 / .550
Shelf * Store / 30.114 / 2 / 15.057 / .807 / .467
Error / 242.667 / 13 / 18.667
Total / 7342.000 / 19
Corrected Total / 746.421 / 18
a. R Squared = .675 (Adjusted R Squared = .550)
Sales
TukeyHSDa,b,c
Shelf / N / Subset
1 / 2
1 / 7 / 13.57
2 / 6 / 17.67
3 / 6 / 25.50
Sig. / .249 / 1.000

Chi-Squared Test; Sample Data made by Alexis Tarter from

Data Set

Procedural Steps

[Analyze]  [Descriptive Statistics]  Crosstabs

Transfer one variable into “Row(s):” and the other variable/s into “Column(s):”

[Statistics] [Chi-Square]  [Continue]

If you want percentages for the table: [Cells]  [Row], [Columns], and [Total]  [Continue]

[OK]