Watch out for these research topics in Statistics and Big data

Watch out for these research topics in Statistics and Big data

Big data is here to stay. But it is no longer a new technology as a lot of firms have already embraced big data; take, for example, Hadoop, which exemplifies an open-source big data project. Think about the following ideas for your next research paper.

  • Harness NoSql and Hadoop to accelerate big data processing.
  • Swift access to data using in-memory concept.
  • Using R programming language for textual data analysis.
  • Statistical analyses of psychological dysfunction on pupil’s academic progress.
  • Interactive and auto-update of R-plot graphs from a webpage without redrawing.
  • Predicting the future using predictive analysis. How big data play a role?
  • Smart big data applications to study the past by way of big data.
  • Using a circular nonparametric method to estimate entropy.
  • Why salaries and expectations of data scientists and data engineers are high?
  • Cybersecurity attacks? Merge Hadoop with SIEM (Security Information and Management) application.
  • Study on the growth of IoT in various industries and sizable impact of IoT on big data.
  • Accelerated Life Testing models: apply stress factors life-testing experiment.
  • Extracting hidden patterns and predicting financial markets thru data mining. Using advanced techniques in statistics.
  • Using survey sampling tools to understand dyslexia in a specific community.
  • Leveraging statistical, computational techniques, neural networks wavelets, and genetic algorithms to solve complex financial issues.
  • Decision theoretic method for getting ranking and selection procedures.
  • Using advanced mathematical concepts of wavelets in econometric modelling.
  • Pharmacodynamics: what are the stochastic models?
  • Natural language processing (NLP) in clinical research: Application of methods to anonymize data.
  • Correlation between employee engagement and employee performance.
  • Analyzing news coverage in politics and identifying patterns.
  • Linear method of the equation: compare and contrast of Gaussian elimination and Cholesky decomposition techniques.
  • Statistical analysis of criminal offenders.
  • Analyzing UK government’s revenue and expenditure.
  • Analyzing the trafficking of children and women and negative effects.
  • An analysis of the benefits of using information technology in bank services to customers.
  • Statistical use of matrices for input and output model and price fixing.
  • A statistical evaluation of the road accident rates on a specific period.
  • A statistical analysis of reported cases of HIV and STD at a particular period of time.
  • A statistical assessment of infant death rates in the state at a certain period of time.
  • Statistical regression analysis on country’s GDP – Europe Vs US.
  • Health impact of asbestos roof panels: a statistical assessment.
  • Statistical study on university pupil’s expenses.
  • Statistical analysis on the impact of pesticides on the microflora of soil classifications.
  • The contrast on fossil fuels and carbon activated from coconuts—a statistical analysis.
  • Critical study on the causes and issues of banking financial distress.
  • An analysis of the merits of using financial reports in evaluating bank’s performance.
  • Solutions for loan defaults in Indian banks: a detailed analysis.

Other research topics may revolve around Bayesian statistics, matching propensity scores, high-dimensional analysis of data, survival data analyses, and, model selections.

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