Statistical & Quantitative Data Analysis Support
With SPSS, R, EViews, SmartPLS and advanced statistical methods — send us your data, and our team analyzes and reports it for you.
Preliminary Analysis
A solid start to the analysis process with data cleaning, missing-data handling and descriptive statistics. This is the starting point if you are analyzing your dataset for the first time or want to confirm your data is reliable before further analysis. You receive a cleaned dataset, a missing-data report and a descriptive statistics table.
Validity & Reliability
Validity and reliability analyses for scale development and adaptation studies. Needed when you are developing a new scale or adapting an existing one to a different sample. We report Cronbach's alpha, item-total correlations and, where needed, exploratory/confirmatory factor analysis results.
Relationships & Correlation
Examining relationships between variables through correlation analysis. Used when you want to see whether a relationship exists between two or more variables, and its direction and strength. You receive correlation coefficients, significance values and an interpreted results report.
Difference Tests
Assessing differences between groups using t-tests, ANOVA and non-parametric tests. Used when you want to compare two or more groups (e.g. experimental-control, gender, age group) on a variable. You receive the appropriate test selection, assumption checks and APA-style interpreted results.
Regression & Structural Equation Modeling
Regression models and structural equation modeling (SEM) with SmartPLS/AMOS. Used when you want to test how much one or more variables predict another, or to test complex variable relationships through a model. You receive model fit indices, path coefficients and the model diagram as part of the full report.
Time Series & Econometrics
Econometric modeling and time-series analysis with EViews. Used when you want to build a forecasting or relationship model with data that changes over time (e.g. inflation, sales, stock price). We report stationarity tests, model estimation and forecast results.
Machine Learning
Machine-learning-supported analysis for classification and prediction models. Used when you need prediction/classification on large or complex datasets where traditional statistical methods fall short. You receive model performance metrics (accuracy, F1 score, etc.) and the code/output files used.
How It Works
Describe your project, we review your data and methodology needs, and send you a quote within 5–7 business days depending on project size. Once you accept, we carry out the analysis and deliver the report.
Our Boundaries
Analizus is not a ghostwriting service. We analyze your data and guide you on methodology; complying with academic integrity rules remains your responsibility.
Frequently Asked Questions
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