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Research and Data Analytics

We help you through the research analysis process of;

  1. Data Requirement Gathering
  2. Data Collection
  3. Data Cleaning
  4. Data entry
  5. Data manipulation and extrapolation
  6. Data Analysis methods:
    • Quantitative analysis Statistical Analysis – involving Descriptive statistics and Inferential statistics from collection, Analysis, interpretation, modelling of data, production and presentation of reports:
      • Frequency tables
      • Custom Tables
      • Correlation analysis
      • Cross-tabulation analysis
      • Chi Square analysis
      • Regression analysis- Linear, binary logistic, probit, logit models etc.
      • Analysis of variance
      • Moderation and mediation analysis
    • Qualitative analysis:
      • Content analysis
      • Narrative and Thematic analysis
      • Discourse analysis
      • Framework analysis
      • Grounded theory
  7. Diagnostic and pilot analysis:
    • Piloting- RELIABILITY and VALIDITY analysis
    • Diagnostics testing:
      • Linearity Test
      • Normality Test
      • Multicollinearity Test
      • Autocorrelation/Serial Correlation
      • Heteroscedasticity
      • Panel root tests
  8. Predictive Analysis and Prescriptive Analysis.
  9. Data Interpretation and reporting- Depending on the type of data in question and the filed of study the researcher is in, the company is endowed with expertise to help the researcher best interpret and report his/her data results, summarize the findings, and present them in a meaningful and the simplest form for the audience in question. We are here to make you understand, make sense and own your research findings to the best of your knowledge and make the audience understand the perspective of your study.
  10. Data Visualization.