For researchers, academics and research teams

Survey Analytics and Research Data Analysis

Your survey is complete. Now comes the question that matters: what can the data honestly tell you? We analyze survey and research data in SPSS, R and Stata and turn it into clear tables, charts and a written interpretation you can defend, from weighting and cross tabulations to regression and significance testing.

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Best forResearchers, NGOs and market research teams

MethodsWeighting, cross tabs, regression, ANOVA

You receiveTables, charts, report and syntax

ToolsSPSS, R, Stata, Excel

The short answer

What does survey data analysis involve?

Survey analysis takes raw responses and turns them into reliable estimates and comparisons. It usually starts with cleaning and coding, then weighting so the sample reflects the population, then descriptive tables and the statistical tests that answer your research questions.

The hard part is choosing methods that suit your design. A test that works for a simple random sample can give misleading results for a clustered or weighted survey, which is why we check the design before running anything.

Roles and handoffs

Where survey analysis fits in your research cycle

Research moves through the same stages whatever the topic. Analysis is only as good as the earlier stages, so we review the plan before fieldwork and do the analysis once the data is clean and coded.

Swipe sideways to see the full diagram

Stage	Who leads	Their work	Where we fit
1. Research question	Principal investigator	Sets the question, outcomes and hypotheses.	Turns the question into testable hypotheses and an analysis plan.
2. Questionnaire	Survey designer	Writes items and the sampling plan.	Checks that each item can be analyzed with the tests you planned.
3. Fieldwork	Field team	Collects responses from the sample.	Monitors response rates and flags problems early.
4. Data entry	Data manager	Records, codes and checks the raw responses.	Validates the file, applies weights where needed and logs every change.
5. Analysis	Data analyst	Runs the planned tests and models.	Runs the analysis in SPSS or R, with assumptions checked and effect sizes reported.
6. Reporting	Research lead	Writes the paper, report or policy brief.	Provides tables, charts and an interpretation you can defend.

Who it is for

Built for teams like yours.

Postgraduate researchers

Methodology guidance and analysis support you can disclose to your supervisor, with every step explained.

Research and policy teams

Robust estimates, subgroup comparisons and tables ready for reports and policy briefs.

NGOs and market research firms

Fast, accurate analysis of household, customer or beneficiary surveys at any scale.

What you get

Clear deliverables, agreed up front.

You receive a complete, reproducible analysis package. Every project is quoted as a fixed price after a free assessment, so you know the cost before work begins.

Data checks and a coding log
Survey weights where the design needs them
Descriptive tables and cross tabulations
Significance tests and regression models matched to your questions
Publication quality charts
A written interpretation with limitations, plus SPSS syntax or R code

Packages and pricing

Pick the depth you need.

Starting prices are shown for each option. Your final price is a fixed quote, agreed after a free assessment of your data and scope, so there are no surprises.

Clear description of your data

Essentials

Descriptive results for a survey that needs a clean, accurate summary.

From $250fixed project

Data check and coding review
Descriptive tables and charts
Cross tabulations for key groups
Short written summary

Get a fixed quote

Recommended for most studies

Standard Analysis

The analysis most research questions need, with results you can defend.

From $550fixed project

Everything in Essentials
Significance tests matched to your data
Regression where the design supports it
APA style tables and interpretation
SPSS or R syntax

Get a fixed quote

For complex or weighted surveys

Full Study

Complete analysis for larger studies, theses and program reports.

From $1,100fixed project

Everything in Standard
Survey weights and design effects
Multiple models and robustness checks
Full results write-up
Review call and one revision round

Get a fixed quote

How it works

Four steps from question to answer.

Step 1
Scope
We agree your research questions, design and outputs.
Step 2
Prepare
Data is cleaned, coded and weighted where needed.
Step 3
Analyze
Tests are chosen to fit the design and assumptions are checked.
Step 4
Report
You receive tables, charts, interpretation and a review call.

Questions we help you answer

If you are asking these, we can help.

Weighting and design effectsCross tabulation and chi square testst tests and ANOVALinear and logistic regressionFactor analysis and scale reliabilityNonparametric testsTrend comparison between survey waves

Tools we use

SPSSRRStudioStataExcelNVivo

?Do attitudes differ significantly between groups?
?Which factors predict satisfaction or adoption?
?How should we weight our sample?
?Is our Likert scale reliable (Cronbach’s alpha)?
?Did results change since the last survey round?
?What can we safely claim from this sample?

FAQ

Questions about Survey Analytics

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Which software will you use for my survey?

We work in SPSS, R and Stata and can deliver in whichever one you or your supervisor prefer, including syntax or code so the analysis can be rerun.

Can you analyze Likert scale data?

Yes. We check scale reliability, choose between parametric and nonparametric tests, and report results in a way reviewers accept.

Do you write the thesis or dissertation for me?

No. We provide analysis support, methodology advice and explanation that you can disclose, in line with your institution’s rules.

How do you handle missing data?

We first measure how much is missing and why, then choose a suitable approach such as complete case analysis or multiple imputation, and document the choice.

Can you handle large national surveys?

Yes. Our team has worked with provincial scale survey data, including weighting, clustering and estimates for subgroups.

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