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Numeric (Quantitative) Data: Analyze data

Analyze data

You have your quantitative data... now what?

UNLV Business Librarian

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Patrick Griffis Business Librarian
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Quantitative Analysis

Quantitative analysis, It is defined as a technique, or methodology, that permits investigators to convert data into numerical format that facilitates statistical analysis of research data.   It allows the quantification of attributes by constructing statistical models to explain observations and serves as a platform for inferring decisions. Researchers employ the quantitative approach for developing knowledge through strategies of inquiry using predetermined instruments such as surveys and experiments. The purpose of quantitative research involves determining the relationship between one variable [independent variable] and another variable [dependent or outcome] within a population. Quantitative research, initially characterized by defining research questions, identifies variables and designs the research methodology before collecting data.  Researchers collect data using structured research instruments extracted from representative population samples. Data analysis, which uses statistical procedures, arranges research data in tables, charts, figures and graphics. There are several statistical software packages that can assist you with you statistical analysis of quantitative data.  See below for more details.  

Babbie, Earl R. The Practice of Social Research. 12th ed. Wadsworth Cengage, 2010

Creswell, John W. Research Design: Qualitative, Quantitative and Mixed Methods Approach, 2nd ed. Sage Publications. 2003.

Quantitative Approaches. Center for Innovation in Research and Teaching.

Quantitative Statistical Software Packages available at UNLV.

Statistical Software Available at UNLV Campus Labs with Statistical Software Packages
Mathematica. Integrated system for computation, modeling, simulation, visualization, development and deployment. CBC_B131  CBC_ C323 TBE_ A311
MATLAB.  High-level language and interactive environment that enables users to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and Fortran. ARC_72  CBC_B131  CBC_C309  CBC_C311   CBC_C321  SU_233  TBE_B310  CBC_B348  CBC_B350  CBC_B367  TEC_112  TEC_113
Mplus. Statistical modeling program that provides researchers with a flexible tool to analyze their data. It offers researchers a wide choice of models,  CEB_211  CEB_212  CEB_309A
R for Windows. Software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. CBC_B131  CBC_C129  CBC_C309  CBC_C311  CBC_C321  CBC_C323  GUA_3202  SU_233  WRI_C211
SAS. Traditional software package for statistical analysis of variance package that uses predictive modeling to exact methods that employs statistical visualization techniques. SAS software designed for both specialized and enterprise level analytical needs.  BHS_131  BEH_102 CBC_B135  GUA_3202  LLB_2141  SU_233
SPSS (IBM). comprehensive statistical package for analyzing any type of data from research projects, from almost any type of file, and use to generate tabulated reports, charts, and plots of distributions and trends, descriptive statistics, and complex statistical analysis. BEH_102  BHS_131  BHS_451  CBC_B131  CBC_B135  CBC_C125  CBC_C129  CBC_C309  CBC_C311  CBC_C321  CBC_C323  CEB_211  CEB_212  CEB_309A  GUA_1125  GUA_3202  LLA_2141  RLL_132  SU_ 233  TBE_A311  TBE_B310  TBE_B348  TBE_B367  TEX-112  TEC_113  WRI_C211
STATA. Complete integrated statistical software package that provides everything you need for data analysis, data management, and graphics. ARC_172  CBC_B131  GUA_3202  LLB_2141  SU_233 


Where to Find Quantitative Statistical Software at University Libraries


Public Terminals

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3. Health Sciences Library, College of Medicine

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Public Terminals

1. Graduate Commons, second floor, Lied Library

2. Health Sciences Library, College of Medicine


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