Rohan M. holds an MSc in Statistics from the University of Mumbai, India, completed in 2014. He has 9 years of experience in statistics, data analysis and R, and he works with students in English, Hindi and Marathi. At FIZ Business Solutions (FIZBS), he provides R statistics assignment help for undergraduate and postgraduate students in the UK and Saudi Arabia.
R is powerful, but students often struggle with error messages, messy data and output that is hard to interpret. Rohan explains code line by line, helps students debug their scripts, and shows how to turn model results into clear written conclusions.
He supports statistics, data science, economics, psychology, biology, public health and business students, from weekly problem sheets to dissertation analysis.
R assignments and modules Rohan supports
Many UK universities now teach statistics through R and RStudio, often alongside or instead of SPSS. Rohan's support covers the tasks students meet most often, listed below.
Modules differ in how much weight they place on code compared with written interpretation. Some mark the script itself, while others focus on the report and treat the code as an appendix. Rohan helps you read your brief carefully so that your effort goes where the marks are.
- Statistics coursework and problem sheets completed in R or R Markdown
- Data cleaning, transformation and visualisation projects
- Regression and statistical modelling reports
- Data science and machine learning assignments using R
- Quantitative analysis for dissertations and research projects
- Reproducible reports with R Markdown or Quarto
- Simulation studies and probability exercises
Key methods, packages and tools
Rohan helps students understand both the statistics and the code behind each analysis. Common areas include:
- Data wrangling with the tidyverse, including dplyr and tidyr
- Visualisation with ggplot2
- Descriptive statistics, t-tests, ANOVA and chi-square tests
- Linear, logistic and Poisson regression with model diagnostics
- Mixed effects models using lme4
- Time series analysis and forecasting
- Principal component analysis, clustering and classification
- Resampling methods such as bootstrapping and cross-validation
- Writing clean, commented and reproducible code
Common mistakes and what UK markers look for
Students frequently lose marks for code that runs but answers the wrong question, for skipping assumption checks, or for pasting console output without interpretation. Other common problems include hard-coded file paths that stop scripts running on another computer, uncommented code, poorly labelled charts, and confusing statistical significance with practical importance.
UK markers typically look for a clear justification of the method, reproducible code, well-presented tables and figures, correct interpretation of coefficients and p-values, and a discussion of limitations. Where code is assessed, they also value readability and sensible structure. Rohan reviews your work with these points in mind and explains how to improve it.
Example projects suited to R
If you have freedom to choose a dataset or question, Rohan can help you pick something that fits your module and word count. Examples include:
- Modelling factors linked to hospital readmission using logistic regression
- Forecasting monthly retail sales with ARIMA models
- Analysing UK house price trends with public data from the ONS
- Customer segmentation using k-means clustering
- Comparing student performance across teaching methods with mixed effects models
Understanding your code and output
A key part of R statistics assignment help is making sure you can explain your own analysis. Rohan focuses on understanding as well as results: why a function is used, what each argument does, and how to read the model summary.
He can help you debug common errors, restructure long scripts into clear steps, and present results in tables and plots that suit an academic report. This is especially useful if you need to discuss your analysis with a supervisor or present it in a viva.
Students who are new to programming often benefit most from this kind of R statistics assignment help, because it builds the confidence to tackle the next problem sheet independently.
How working with FIZBS works
Share your brief, dataset and any starter code on WhatsApp. FIZBS reviews the task and confirms whether Rohan is available for your deadline.
You get a clear price from £20 per 1,000 words, depending on level, complexity and timeframe. You pay 50% to start and 50% on completion, with updates until the deadline.
Support can include explanation of methods, code review and debugging guidance, interpretation of output, and editing of your written report.