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Descriptive Analysis: http://calcnet.mth.cmich.edu/org/spss/Prj_New_DrugData.htm
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 GenderBefore_exp
_BPAfter_exp_
BPN Valid 50 50 50 50
Missing 0 0 0 0Mean 61.48 98.3020 88.5980Std. Error of Mean
.920 .73082 .64507
Compute New Variables http://calcnet.mth.cmich.edu/org/spss/Prj_New_DrugData.htm
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) http://calcnet.mth.cmich.edu/org/spss/Prj_New_DrugData.htm
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 http://calcnet.mth.cmich.edu/org/spss/Prj_body_fat_data.htm
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 http://calcnet.mth.cmich.edu/org/spss/Prj_body_fat_data.htm
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 http://calcnet.mth.cmich.edu/org/spss/Prj_body_fat_data.htm
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 ANOVA Data 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
Tukey HSDa
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 http://calcnet.mth.cmich.edu/org/spss/Prj_Super_MarketData.htm
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
Tukey HSDa,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 http://www.ling.upenn.edu/~clight/chisquared.htm
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]
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