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R Programming Language is a programming language used for statistical computing and advanced data analysis. It is the language of choice for many data analysts and statisticians, allowing them to work with large amounts of data quickly and efficiently. The language provides a platform for manipulating, displaying and presenting statistical datasets related to various disciplines such as mathematics, computer science and engineering.
An R Programmer can create many types of statistical calculations such as linear and nonlinear models, hypothesis tests and experiments, clustering, classification and regression trees. Additionally, they can make custom metrics more accessible through the writing of functions, plots and charts to make them easier to read and interpret. Plus they can take data from various sources like text files, database systems or HTML webpages and transform it into tidy sets ready for further action. Of course all of this can be done with careful formatting in order to achieve the best possible results unlocking valuable insights from ever-increasing amounts of data around us.
Here's some projects that our expert R Programmers made real:
By hiring an R programmer on Freelancer.com, you get access to a versatile set of solutions tailored specifically to your needs that help you make sense of your data in a more meaningful way. This way you can draw important conclusions easily while freeing up resources that you can use in other endeavors. So if your business requires someone experienced in R Programming Language then why not give it a try and post your project on Freelancer.com?
From 41,479 reviews, clients rate our R Programmers 4.8 out of 5 stars.R Programming Language is a programming language used for statistical computing and advanced data analysis. It is the language of choice for many data analysts and statisticians, allowing them to work with large amounts of data quickly and efficiently. The language provides a platform for manipulating, displaying and presenting statistical datasets related to various disciplines such as mathematics, computer science and engineering.
An R Programmer can create many types of statistical calculations such as linear and nonlinear models, hypothesis tests and experiments, clustering, classification and regression trees. Additionally, they can make custom metrics more accessible through the writing of functions, plots and charts to make them easier to read and interpret. Plus they can take data from various sources like text files, database systems or HTML webpages and transform it into tidy sets ready for further action. Of course all of this can be done with careful formatting in order to achieve the best possible results unlocking valuable insights from ever-increasing amounts of data around us.
Here's some projects that our expert R Programmers made real:
By hiring an R programmer on Freelancer.com, you get access to a versatile set of solutions tailored specifically to your needs that help you make sense of your data in a more meaningful way. This way you can draw important conclusions easily while freeing up resources that you can use in other endeavors. So if your business requires someone experienced in R Programming Language then why not give it a try and post your project on Freelancer.com?
From 41,479 reviews, clients rate our R Programmers 4.8 out of 5 stars.The paper is already outlined and the dataset—purely observational—has been cleaned and is ready to load into R. What remains is the core empirical work: applying a Difference-in-Differences strategy, interpreting the findings, and writing up the Results and Discussion sections so they flow naturally with the rest of the manuscript. Scope of work You will run the DiD models in R (base, tidyverse, or workflows are all fine) and include any necessary robustness checks or placebo tests. Once the estimates are solid, weave the numbers, tables, and plots into a coherent narrative that completes both the Results and the Discussion, linking back to the hypotheses already laid out in the introduction. Deliverables • Reproducible R script or R Markdown file with all code and...
I need help with a data analysis homework task using R. Requirements: - Experience with R - Knowledge of statistical analysis and data interpretation - Ability to explain concepts clearly Please provide examples of previous work.
The use of data and machine learning has become increasingly common in professional sports, especially in the NBA. Teams now collect and analyse large amounts of historical data related to games, players, and overall performance in order to gain a competitive advantage. As the data is well structured and widely available, the NBA has become a popular area for sports analytics and predictive modelling. Most existing basketball analysis focuses on team statistics and individual player performance, such as scoring, shooting efficiency, and defensive contributions. While these metrics are useful, basketball is a team sport, and success often depends on how well players perform together on the court. This is team chemistry, but it is difficult to measure using traditional statistics.
Project requirements 1) Submission package Report files Part 1 report: maximum 2 pages Part 2 report: maximum 6 pages Page limits include figures and tables Page limits exclude title page, table of contents, and references The report must include explanations suitable for readers not familiar with programming Report must be submitted as PDF (or other allowed document format as specified by your portal) Code files (reproducible) Python code must be provided as Jupyter notebook(s) (.ipynb) R code must be provided as RMarkdown (.Rmd) if required by the brief Code must be runnable by someone else to reproduce your results If you reuse outputs or cleaned data from earlier questions, you must reference them clearly Submission location All relevant files must be submitted to the des...
Basically there are two task in this project. 1: I have a research paper written with the help of AI, and it needs to be re-written in human style patter so that it bypass the AI detection. 2: In the research paper, there is a section of analysis of a dataset using R. That analysis also needs to be done and three hypothesis needs to be tested with results written without AI language detection. I have a numerical dataset ready for a full hypothesis-testing workflow in R. The job covers three specific tests—t-tests, Chi-square tests and ANOVA—applied where each is statistically appropriate. I will supply the cleaned data and any relevant codebook; you return a well-commented R script (base R or tidyverse is fine) that reproduces every step, plus a concise write-up that reads lik...
I need an expert to analyze daily rainfall data for my farm and build a predictive model. The analysis should cover: - Trend analysis - Anomaly detection - Seasonal patterns assessment The goal is to develop a robust rainfall prediction model. Ideal skills and experience include: - Proficiency in data analysis and statistics - Experience with predictive modeling - Knowledge of agricultural impacts of rainfall patterns - Familiarity with relevant software and tools (e.g., Python, R, etc.) The data is very erratic so I dont need a detailed monthly prediction model although it would be nice if possible, otherwise a yearly prediction model or atleast something that says a dry season is coming or a wet season is coming. The model must include macro environmental factors such as El Nino (ONI...
**Project Title:** Machine Learning Model to Analyze Price Behaviour Around Moving Average (Forex – XAUUSD) **Project Description:** We are building a quantitative research project focused on understanding and modeling **price behaviour around a Moving Average** using machine learning techniques. The objective is to develop a **statistical/ML model that can estimate the probability and confidence of price movement relative to a moving average**. This project is specifically focused on **XAUUSD (Gold) in the Forex market**, using **1-minute historical data**. The key requirement is that the **model must analyze price dynamics strictly around the Moving Average**, without relying on additional technical indicators such as RSI, MACD, Bollinger Bands, etc. We want to understand and ...
I’m working on a school assignment that must be completed in R Studio and centres on running a linear regression. The dataset is ready to share, and the goal is to: • write a clear, R script that imports the data, checks basic assumptions, fits the linear model, and outputs tidy results • provide concise explanations of each step so I can understand the rationale behind the code • include a brief write-up (Word is fine) that summarises findings, highlights any limitations, and suggests next steps Please keep the code beginner-friendly—base R or tidyverse is fine—and make sure every command is reproducible in R Studio. If you’ve helped students with regression assignments before, I’d love to see a quick sample or hear how you’d struc...
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