Comprehensive Research Methodology Report: Wireless LAN Analysis

This report outlines the research methodology employed for a Wireless LAN study. The research design utilizes secondary research, drawing upon existing sources to analyze trends, challenges, and comparisons related to wireless LAN technology. Data collection involves systematic sampling of secondary sources, including websites like CISCO and CCNA, and reports from telecommunication companies. Both qualitative and quantitative data are considered, with a mixed-method approach to mitigate potential biases. Data analysis is conducted using the Statistical Package for Social Sciences (SPSS), enabling the conversion of qualitative data into statistical packages for analysis. The SPSS technique facilitates descriptive statistics, missing value analysis, and advanced inferential and multivariate statistical procedures to derive meaningful findings and results. The report emphasizes the importance of data interpretation and the application of statistical tools to draw insightful conclusions about the wireless LAN landscape.

Running head: RESEARCH METHODOLOGY 1
Wireless LAN research
Research methodology
Student’s Name
Institutional Affiliation
Professor’s Name
Date

RESEARCH METHODOLOGY 2
Research methodology
Research Design
The study would deploy the use of secondary research strategies, which involves the
collection of data from secondary sources (Bell, Bryman, & Harley, 2018). The secondary
research design would be advantageous in that the wide range of existing sources would enable
the research to make references and comparison between the different sources inclined to the
topic of study. Concisely, the use of the secondary materials would provide insightful meaning to
the topic of research within a minimal time due to their availability. The method was selected
over the primary design since it is based on evidence of the existing findings from other studies.
Additionally, the records found from different telecommunication organizations and firms would
enable the research to have adequate samples of data, which would depict many variables such as
the trends in performances and the changes brought by the wireless LAN. Other variables would
include the challenges faced in the implementation of wireless LAN among the employees and
the comparison of the technology with the previous systems among others.
Data collection method
The suitable methods of data collection would be the systematic sampling of the existing
secondary sources. The research would apply for systematic literature review through the
application of appropriate inclusion and exclusion criteria to come up with the relevant
secondary sources. The selection criteria would use the relevance of the titles and abstract
abstracts of different articles that are pertinent to the wireless LAN study topic. The electronic
search would be conducted in various websites and databases such as CISCO, CCNA and CNET
among others that would be relied upon for suitable research study. Moreover, the research

RESEARCH METHODOLOGY 3
would depend upon the reports from different organisations concerning the use of the wireless
LAN technology or the telecom companies that provide the services to the companies.
However, both the qualitative and the quantitative data would be considered during
collection for evaluation and analysis. The mixed method approach would enable the researcher
to draw qualitative judgments to the numerical data as well as eliminate the disadvantages of
using one set of data. Through the mixed method of data collection, the research would also be
able to forego the potential biases of either qualitative or quantitative data. The data would be
subject to analysis and interpretation as explained in the section below.
Data analysis
After the collection of data, the Statistical Package for Social Sciences (SPSS) would be
used to carry out data analysis (Whittier, Wildhagen, & Gold, 2020). Using this technique, the
researcher would be able to convert the qualitative data that was collected along with the
numerical data into statistical packages for analysis. The tool would perform various descriptive
statistics using techniques such as cross tabulation, t-tests, ANOVA, and Chi-Square among
others that would provide inferences to the data analysed into meaningful information.
Additionally, using the SPSS technique, the researcher can perform missing value analysis,
which is an approach that helps in making better about the data. The missing value analysis
would enable the researcher to fill the missing blanks within the data sets thus creating better
models of estimating the missing data. After obtaining the missing data sets, sophisticated
inferential and multivariate statistical procedures such as analysis of variance, discriminant
analysis, and factor analyses to the data to give appropriate findings and results.

RESEARCH METHODOLOGY 4
References
Bell, E., Bryman, A., & Harley, B. (2018). Business research methods. London: Oxford
university press.
Whittier, N., Wildhagen, T., & Gold, H. J. (2020). Statistics for Social Understanding: With
Stata and SPSS. Maryland: Rowman & Littlefield Publishers.