Statistical Analysis

Statistical Analysis Services

Scopus Publication Support Center provides professional statistical analysis support for faculty members, researchers, research teams, PhD candidates, and master’s students who need accurate, clear, and academically defensible data analysis for manuscripts, theses, dissertations, reviewer responses, and publication-ready research outputs.

This service is suitable for clients at different stages, whether they are preparing a journal manuscript, analyzing thesis or dissertation data, responding to reviewer comments, developing research results, or improving the statistical quality of an academic paper before submission.

Our goal is not only to generate statistical outputs, but also to connect the research questions, hypotheses, variables, methodology, analysis procedures, results, tables, figures, and interpretation in a clear academic format.

Who This Service Is For

Faculty Members: researchers preparing manuscripts, funded projects, institutional studies, or journal submissions that require statistical analysis or results improvement.
Researchers: authors who have collected data and need analysis, interpretation, results tables, or publication-ready reporting.
Research Teams: teams working on collaborative projects, surveys, experimental studies, applied research, or manuscripts requiring advanced analysis.
PhD Candidates: doctoral students who need dissertation data analysis, advanced methods, SEM, qualitative analysis, mixed-methods support, or publication-oriented results reporting.
Master’s Students: students who need clear and accurate analysis for thesis data, proposal alignment, results chapters, or thesis-to-article development.
Authors Responding to Reviewers: researchers who need additional analysis, robustness checks, clarification, revised tables, or statistical explanations requested by reviewers.

What We Can Help With

1. Data Screening and Preparation

Before analysis begins, we review whether the data are ready for reliable analysis. This step helps identify problems that may affect the validity of the results.

Data cleaning
Variable coding
Missing data review
Outlier detection
Data consistency checks
Normality checks when required
Data structure review
Preparation of data for SPSS, AMOS, SmartPLS, R, Python, Excel, or other tools

2. Descriptive Statistics

We prepare descriptive results that summarize the sample, variables, and main research measures clearly.

Frequencies and percentages
Means and standard deviations
Minimum and maximum values
Demographic profile tables
Charts and visual summaries
Descriptive interpretation for theses, dissertations, or manuscripts

3. Reliability and Validity Analysis

We support reliability and validity checks when the study uses questionnaires, scales, constructs, or measurement instruments.

Cronbach’s Alpha
Composite reliability
Average variance extracted
Item-total statistics
Exploratory factor analysis
Confirmatory factor analysis
Convergent validity
Discriminant validity
Measurement model assessment

4. Hypothesis Testing

We help select and conduct appropriate statistical tests based on the study design, variable types, sample size, and research questions.

Independent samples t-test
Paired samples t-test
One-way ANOVA
MANOVA
Chi-square test
Correlation analysis
Simple linear regression
Multiple regression
Logistic regression
Mediation analysis
Moderation analysis
Path analysis
Structural equation modeling

5. Advanced Statistical Analysis

For advanced theses, dissertations, and journal manuscripts, we provide support for more complex statistical procedures and publication-oriented analysis.

SEM using AMOS
PLS-SEM using SmartPLS
Regression models
Mediation and moderation models
Model fit assessment
Path coefficients and effect interpretation
Robustness checks when appropriate
Sensitivity analysis when appropriate
Reviewer-requested additional analysis
R or Python-based analysis when required

6. Qualitative Analysis

We also support qualitative and mixed-methods research projects that require systematic interpretation of interview, focus group, observation, or textual data.

Interview transcript review
Focus group analysis
Thematic analysis
Content analysis
Codebook development
Theme extraction
Evidence tables
Qualitative results narrative
NVivo or MAXQDA support when applicable
Integration of qualitative and quantitative findings in mixed-methods studies

7. Results Reporting and Interpretation

We help present the analysis in a clear academic format suitable for research papers, theses, dissertations, and reviewer responses.

Results tables
Publication-ready statistical tables
Figures and charts when appropriate
Hypothesis summary tables
Interpretation of findings
Explanation of statistical significance
Results section support
Connection between results and research questions or hypotheses
Reviewer-response statistical explanations

Software and Tools We May Support

SPSS
AMOS
SmartPLS
Excel
R
Python
NVivo
MAXQDA
Other tools depending on the project requirements

Common Statistical Analysis Requests

Analyze thesis or dissertation data
Analyze survey data for a journal manuscript
Prepare statistical tables for publication
Check reliability and validity of a questionnaire
Test research hypotheses
Run regression, mediation, moderation, SEM, or PLS-SEM
Interpret SPSS, AMOS, SmartPLS, R, or Python outputs
Respond to reviewer comments about statistical analysis
Revise tables and results after journal review
Prepare results for thesis-to-article or dissertation-to-publication development
Conduct qualitative coding or thematic analysis
Prepare results chapter or manuscript results section support

What You May Receive

Data screening notes
Cleaned or prepared data file when applicable
Statistical output files
Analysis report
Results tables
Figures or charts when required
Hypothesis testing summary
Reliability and validity results
SEM or SmartPLS model results when applicable
Qualitative codes and themes when applicable
Interpretation of results
Results section support for thesis, dissertation, or manuscript use
Reviewer-response analysis explanation when applicable

What We Need from You

To assess your statistical analysis request accurately, please provide any available materials, such as:

Data file, such as Excel, SPSS, CSV, or other format
Research questions or hypotheses
Variable names and descriptions
Questionnaire, scale, interview guide, or research instrument
Methodology section, if available
Proposal or manuscript draft, if available
Required statistical tests, if specified by your supervisor, reviewer, or journal
Supervisor comments or reviewer comments, if available
Target journal guidelines, if the analysis is for publication
Required software, if any
Deadline

If you are not sure which analysis is required, you may submit your data file, research questions, methodology, and a short explanation of your study, and we will recommend the most suitable analysis approach.

How the Statistical Analysis Process Works

Submit your request: upload your data file, research questions or hypotheses, instrument, methodology, and any relevant instructions.
Initial assessment: we review the data structure, research design, variables, required analysis, and deadline.
Scope and quote: we provide a clear recommendation, expected analysis, deliverables, timeline, and price.
Analysis execution: the analysis is conducted according to the approved scope and suitable statistical methods.
Results reporting: you receive the agreed outputs, tables, interpretations, and report files.
Revision support: minor clarifications or corrections within the agreed scope may be provided when needed.

Ethical Boundaries

Scopus Publication Support Center analyzes real data provided by the client. We do not fabricate data, invent results, manipulate findings, remove inconvenient results, or change outputs to match a desired conclusion.

Clients remain responsible for the accuracy, legitimacy, ethical approval, data ownership, and final use of their research data and results.

Services & Starting Prices

The following prices are starting points. Final pricing depends on the data size, number of variables, research complexity, required tests, software, reporting needs, deadline, and level of expert review required.

Data Screening: starting from $50
Descriptive Statistics: starting from $100
Reliability and Validity Analysis: starting from $120
Basic SPSS Analysis: starting from $150
Hypothesis Testing Package: starting from $250
Regression Analysis: starting from $250
Mediation or Moderation Analysis: starting from $300
SEM / AMOS / SmartPLS: starting from $400
Qualitative Analysis: starting from $300
Full Results Report: starting from $350
Reviewer-Requested Additional Analysis: custom quote
Full Statistical Analysis Package: custom quote

Important: Final prices are confirmed only after reviewing the data file, research requirements, and expected deliverables.

Start Your Statistical Analysis Request

Submit your data file, research questions or hypotheses, variable descriptions, questionnaire or instrument, methodology section, and any supervisor, reviewer, journal, or university instructions for initial assessment.

After reviewing your request, Scopus Publication Support Center will provide a clear recommendation, scope of work, timeline, deliverables, and quote.