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Unit 1 Individual Project
An Overview of SPSS Statistics Tool
ThienSi (TS) Le
Colorado Technical University
RES 814-1601C-02: Quantitative Research Methods
Professor: Dr. Mary Lind
January 18, 2016

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Abstract
Unit 1 of the Course RES814 -1601C-02 Qualitative Research Methods focuses on
utilizing software tool SPSS to aid in the analysis of quantitative data. The Unit 1
Individual Project (U1 IP) document provides basic proficiency in the development of
research strategy and design of quantitative studies. It consists of four parts:
A. Basic Use of SPSS
B. Finding Dataset and Rationale
C. Summary
References
Keywords: Analysis model; analytical software; analytics; dataset; data sources;
statistical tools; statistics.

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An Overview of SPSS Statistics Software Tool
In Quantitative Research Methods (Qn), researchers usually use analytical
software tools to analyze large data sets statistically. One of analytical software tools is
the IBM SPSS Statistics (Statistical Package for the Social Sciences) widely used today.
SPSS is used in statistical analysis, data management, and data documentation (Field,
2015). Its base software consists of four types of statistics:
- Descriptive statistics: Cross tabulation, Frequencies, Descriptive Ratio Statistics, etc.
- Bivariate statistics: Means, t-test, ANOVA, Correlation, Nonparametric Tests, etc.
- Prediction for numerical outcomes: Linear regression.
- Prediction for identifying groups: Factor analysis, cluster analysis, Discriminant, etc.
SPSS is an IBM product, the released version 23 on March 3, 2015. It uses a Java
platform in operating systems (OS) such as Windows, Linux, Unix and Mac. Its website
is www.ibm.com/software/analytics/spss (Schumacker, 2015). Notice that there are other
analytics tools such as R Project, Tableau that are also widely used today (Schumacker,
2015).
A. Basic Use of SPSS
In this course Quantitative Research Methods, SPSS software will be used to most
of the Qn analysis. The basic use of SPSS are the responses to three comprehensive
questions below:
1. What are variables and in what ways can you enter data into SPSS?
In general, a variable is a name or symbol that may assume any given value or set
of values with appropriate attributes. In SPSS, Data Editor has many cells that can
contain data for a dataset. In Data View, data that are called entries, records, are rows,

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and variables are the columns. In Variable View, the user enters data such as Name,
Type, Width, Values, etc. for variables. Simple rule for variables in Data Editor is data or
information from different entries or records go in different rows, whereas data from the
same variables is stored in various columns (Field, 2015).
2. Once you have numeric data into SPSS, what steps are required to define the
meanings of the numbers for SPSS? (This requires explaining the components of Variable
View in SPSS.)
To define the meanings of the numbers for SPSS, user creates variables in
Variable View. Each row in this Variable View stands for a variable with a set of
characteristics in labeled columns. These labeled columns consists of 11 characteristics of
each variable:
- Name: Symbol or name of a variable.
- Type: Different type of data such as number, string, currency, etc.
- Width: 8 characters and up to 32,768.
- Decimals: 0 to 16
- Label: name of a variable.
- Missing: For missing data
- Columns: Width of the columns
- Align: Set alignment
- Measures: Levels of a variable.
- Role: Analysis can run automatically.

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After entering data in the rows for entries, records, and the columns for variables,
the user should give a dataset a name, choose an appropriate director, and save all data in
the dataset.
3. Why is it important to SPSS that you define these meanings?
It is important to SPSS that the data and variables are defined properly because of
several reasons:
- Ensure that a dataset is consistent and stable.
- Dataset’s data is safe and reliable.
- Maintain a consistent dataset for later updating or modifying data.
- SPSS statistical functions will use these data to carry out the statistical analysis.
- Ensure the accurate output results.
- Minimize the cost of maintenance.
B. Finding Dataset and Rationale
1. Review the Key Assignment Requirements (Unit 5 Individual Project).
Unit 5 Individual Project (U5 IP) that will be due in week 5 is a quantitative
report writing. It consists of two parts:
- Part 1: It requires to conduct a literature search and write an introduction and
literature on the topic of research.
- Part2: It is a key assignment that requires using SPSS on database. Students will
develop a set of hypotheses related to the database then use SPSS to analyze data.
The full report in APA format includes six sections: Abstract, Introduction,
Methods, Results, Discussion and Conclusion, and References.
2. Identify a data set that you might use for the final assignment.

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Which variables interest you? What type of relationship might exist between the
variables?
Several datasets (electric,sav, endorph.sav, country.sav) from dataset.zip of this
course were explored. It appears that a dataset “country.sav” is more interesting to
compare and contrast general living life in each country. It contains data and information
of the world (122 countries).
In this dataset “country.sav”, some variables such as GDP, life expectancies,
hospital bed, doctors per 100000, infant mortality rate, death rate, etc. are interesting.
They reflect how comfortable and secure people live in the countries.
These variables represent basic living standard, social security, welfare, and
hospitality that citizens live in the country.
3. Explain your rationale for selecting this data set.
The dataset “country.sav was selected because of several reasons:
- The dataset’s data and information are useful for generic worldview.
- The selected dataset is not so big but also not so small for amateurs’ statistical
analysis. It makes the student more comfortable to work in statistics.
- There are not many missing data that may steer the analysis less accurate.
- It gives a general view of people who live in these countries.
- It reflects living standard in each country.
- It covers the world that includes 122 countries registered in UN.
- It provides statistical data on the gross domestic product, life expectancy, birth
rate, death rate, doctors for patients, available hospitals, etc. in each country.
- Information may help people want to work and live in certain countries.

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Notice that this dataset (country.sav) does not contain information on education
level and government as a whole that may define political democracy, human rights or
some fundamental freedoms for citizens.
C. Summary
This Unit 1 Individual Project Paper provided an overview of IBM SPSS
Statistics and some basic operations on inputting data and information of records in rows
and variables in columns in Data Editor. It presented an opportunity for students to an
overview of the final project, Unit 5 Individual Project and prepared a dataset ahead
along this course. The document also provided what type of relationship between
variables in SPSS and rationale why a student chose this dataset “country.sav” in Unit 1
assignment.

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REFERENCES
Field, A. (2015). Discovering Statistics using IBM SPSS Statistics. SAGE Publications.
Huck, S. (2015). Reading statistics and research. New Jersey, NJ: Pearson.
Schumacker, R. E. (2015). Learning statistics using R. SAGE Publications.