This document outlines elements of developing a data analysis plan, including defining data analysis, common analysis methods, and key components of an effective plan. It discusses: 1) Quantitative and qualitative analysis methods like descriptive statistics and thematic analysis. 2) Key elements of a plan such as research questions, variables, proposed analyses, and presenting findings. 3) Developing a plan by identifying questions and variables, choosing analyses, and stating how results will be reported.

1. Session 9: Developing a data analysis
plan
Module Code: NMT 06106
Module Name: Fundamentals of Research

2. Learning Tasks
By the end of this session a learner is expected to be able to:
• Define data analysis and data analysis plan
• Explain data analysis methods/techniques
• Outline elements of data analysis plan
• Develop data analysis plan

3. Brainstorming
• Define the terms “data analysis” and “data analysis plan”.
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4. Definition
Concepts of data analysis
• Data analysis is a method or process of applying graphical, statistical,
quantitative or qualitative techniques to a set of observations or data
in order to summarize it or to find general patterns
• Data analysis plan is a plan for analysing a set of collected data

5. Common Data Analysis Methods
• Once data are collected using acceptable methods and tools, they
need to be analyzed using suitable analysis methods to generate
meaningful information
• The main objective of analyzing data is to provide answers that will
help in answering research questions and meet research objectives

6. Common Data Analysis Methods
There are two broad categories of data analysis methods commonly
used in research:
• Quantitative data analyses
• Qualitative data analyses

7. Common Data Analysis Methods
Quantitative data analyses
Before quantitative data are analysed, the data need to be:
• Checked for completeness and missing values/data
• Checked for accuracy and errors
• Coded for analysis
In quantitative data analyses, there are two methods that are
commonly used to analyse data:
• Descriptive data analyses
• Inferential data analyses.

8. Common Data Analysis Methods
Quantitative analysis can be done using two approaches(modes):
• Computer software- assisted analyses
• Manual analysis, not using a computer or software

9. Common Data Analysis Methods
• Descriptive data analyses are data analyses that focus on analysing a
set of collected data in order to obtain descriptive statistics such as
frequencies, mean, median, mode, and standard deviation.
• Inferential data analyses (statistical significance tests) are group of
statistical techniques that help researchers to determine associations,
correlations or causal relationships among two or more variables in a
research.

10. Common Data Analysis Methods
Qualitative data analyses
• There are many ways of analysing qualitative data, but the commonly
used method is thematic analysis framework

11. Common Data Analysis Methods
• Thematic analysis has the following steps:
• Preparing and organizing data for analysis;
• Determining how data analysis will be done;
• Familiarizing with the general sense of the data;
• Developing code and coding the data; using code to develop description and
themes;
• Relating and developing second layer themes which are broader;
• Summarizing and reporting findings
• Qualitative analysis can also be manually and by using computer
software such as N-Vivo software

12. Elements of Data Analysis Plan
• Data analysis plan provide guidance on planned data analysis
The data analysis plan has the following elements:
• Research questions or objectives: this element typically indicate the
research question or objectives that the research need to answer or
meet
• Variables: this element indicates all types that are needed to describe
the sample, answer research questions and meet research objectives

13. Elements of Data Analysis Plan
• Proposed data analysis: this element of the plan show type of data
analysis and specific tests that will be performed to generate findings
to answer research questions or meet research objectives
• Methods of presentation findings: this element states how the
findings will be presented in order to answer the research questions
or meet research objectives; the presentation can be done in
numerically, textually, diagrammatically using tables, figure or graphs.

14. Developing a Data Analysis Plan
The data analysis plan can be in three forms:
• Narrative form: described using words/texts
• Table form: presented in acceptable table
• Both in narrative and tabular in form: described in text and presented
in a table

15. Developing a Data Analysis Plan
The steps for developing a data analysis plan as follows:
• Identify and write the research question to be answered or research
objective to be address : e.g. to determine the proportion of women of
reproductive age using modern planning methods in Village.
• Identify and write the needed variable/data to answer each research
question or meet the research objective; for example the number of
women in reproductive age using modern family planning methods
and total number of women in reproductive age included in a research

16. Developing a Data Analysis Plan
• Identify and write methods of data analysis that will be performed to
answer each research question or meet the research objective.
Example descriptive analysis
• State how the findings will be presented in the research report.
Example for data related to the above variable above may presented
numerically (%) and textually.

17. Format for developing a data analysis plan
Research
question or
objective
Variables Proposed data
analysis
Methods of
presentation
findings
To determine the
proportion of
women of
reproductive age
using modern
family planning
methods in Village
 Number of women in
reproductive age using
modern family planning
methods (numerator)
 Total number of women
in reproductive age (
denominator)
Descriptive
analysis (% of
women of
reproductive age
using modern
family planning
methods
Numerically
(%) and in text

18. Key Points
• Data analysis is a basic element of research methods
• There are two main categories of data analyses used by researchers
• It is important include essential elements of data analysis plan in a
data analysis section of a proposal

19. Session Evaluation
• What is data analysis?
• What are the three elements of data analysis plan?
• What are two main categories of data analysis methods?

20. Assignment
Write a data analysis plan or section of your proposal to cover the
following:
• Variables for the research
• Specific data analysis methods
• Presentation of findings
Instruction: This assignment will be presented in the next session or
submitted to facilitators for comments and suggestions.