This beginner's manual for students, researchers, and data analysts provide a visual step-by-step approach for conducting data analysis using the Statistical Package for the Social Sciences (SPSS). It uses screen captures of the software to simplify the steps needed to carry out the commands to perform the statistical methods commonly employed in data analysis.

1. Daniel F. Sarpong, PhD
CEO, Biostatistician & Educator
Illustrative Example:
Two-Sample Independent T-Test

2. Presentation Outline
 Purpose of Presentation:
 Demonstrate a Visual Step-by-Step Process of Conducting Two
Independent Sample T-Test using SPSS.
 Concise Description of the Practice Dataset
 Format of the illustrative Example:
 Problem Statement
 Stating the Null & Alternative Hypotheses
 Identification of Appropriate Statistical Method
 Underline Assumptions the Appropriate Statistical Method
 Visual Step-By-Step Process of Using SPSS for Data Analysis
 SPSS Output
 Interpretation of Findings

3. Practice Dataset
 The Practice Dataset was extracted from a
Framingham Heart Study Teaching Dataset, which was
created for instructional purposes.
 Source: https://biolincc.nhlbi.nih.gov/teaching/
 The Practice Dataset used to demonstrate the use of
conducting data analysis using SPSS has a 100
participants.
 Data elements: participant ID (PID), gender, age (in
years), body mass index (BMI; kg/m2), systolic blood
pressure (SBP; mmHg), diastolic blood pressure (DBP;
mmHg), total cholesterol (TCHOL; mg/dL), plasma
glucose (Glucose; mg/dL), diabetes mellitus (DM) and
hypertension (HTN).

4. Sample of the Practice Dataset

5. Problem: Using the Practice Dataset,
determine if there is gender difference as
it relates to systolic blood pressure (SBP)
of the target population. Significance
test is performed at the 0.05 significance
level.
Null and Alternative Hypotheses:
The null and alternative hypotheses are:
 H0: µ 𝑀 = µ 𝐹 vs. H1: µ 𝑀 ≠ µ 𝐹
 where µ 𝑀 = mean SBP for males and µ 𝐹= mean SBP for
females.

6. Data/Information Provided &
Assumptions (if Applicable)
 Identification of Appropriate Statistical
Method: Two Independent Sample T-Test. The
two independent groups are defined by sex (male
and female).
 Data/Information: Information/data extracted based
on the problem are as follows.
 Dependent variable: SBP; which is continuous
 Independent variable: two groups defined by sex.
 Significance level, α = 0.05
 Hypothesis is two-sided

7. Data/Information Provided &
Assumptions (if Applicable)
 Assumptions: The two independent sample t-test
is valid if these assumptions are satisfied.
 The data, SBP, is continuous.
 The probability distribution of SBP is normal.
 The independent variable should be categorical with
independent two groups.
 The observation within and between the groups
should be independent. This assumption is achieved
by randomly selecting the samples from the two
respective populations.
 Homogeneity of variances – the variances of the two
groups should be the same.
 The Levene’s Test of Equality of Variances is used to test
for this assumption.

11. Interpretation of Findings
 To test H0: µ 𝑀 = µ 𝐹 vs. H1: µ 𝑀 ≠ µ 𝐹, first examine the
Levene’s test of equality of variances to determine if the
variances of the two groups are the same (H0:𝜎 𝑀
2
= 𝜎 𝐹
2
vs.
H1: 𝜎 𝑀
2
≠ 𝜎 𝐹
2
).
Since the p-value of the Levene’s Test equals 0.003 (< 0.05),
the test is significant hence, H0:𝜎 𝑀
2
= 𝜎 𝐹
2
is rejected and you
conclude in favor of H1:𝜎 𝑀
2
≠ 𝜎 𝐹
2
; the variances are unequal.

12. Interpretation of Findings
 Using the unequal variance t-test to test the
hypothesis: H0: µ 𝑀 = µ 𝐹 vs. H1: µ 𝑀 ≠ µ 𝐹 we fail to
rejected H0: µ 𝑀 = µ 𝐹 since the p-value (p=0.151)
associated with the unequal variance t-test is greater
than 0.05.
 Hence, we conclude there is no significant gender
difference in systolic blood pressure.

13. For More Information!
 Presentation is extracted from the text:
 Data Analysis Using SPSS: Visual Step-By-Step
Process Manual One [© 2016] .
 Publisher: Creative Force Publishing Company
 ISBN: 978-0-9969873-9-4
 Author: Daniel F. Sarpong, PhD
 CEO, Educator & Biostatistician
For additional chapters in the textbook contact Amazon.com --
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