Statistics Jobs

I need a clear, insight-driven analysis of my customer data with one objective in mind: pinpoint where we can lift overall satisfaction. You’ll receive anonymised purchase history, support-ticket logs, and survey scores in CSV format; from there I expect you to uncover trends, pain points, and the factors most strongly correlated with happy—or unhappy—customers. Your final hand-off should include: • A concise written summary of key findings, plainly tied to customer-experience improvements • Visualisations or dashboards that let a non-analyst grasp the story quickly • Actionable recommendations ranked by impact and effort SQL and either Python (pandas, scikit-learn) or R are the preferred tools, but if you have a proven workflow in something else th...

I already hold a raw-data workbook that lists each product, its department and the associated revenue, plus a separate sheet with customer details. What I need now is to turn those rows into insight while watching the entire process in real time. Here is what I want us to tackle together: • Spot revenue trends month-over-month and year-over-year. • Compare product sales by department so I can instantly see top and under-performers. • Layer in customer demographics to explain the “why” behind the numbers. We will meet on Zoom or Teams, share screen, and co-build both an Excel model (pivot tables, slicers and chart dashboards) and a Power BI report (clean data model, DAX measures, interactive visuals). I will be asking questions throughout, so please be c...

I need an Excel model for financial forecasting, specifically for patient modeling. Key Requirements: - Financial forecasting expertise - Experience in patient modeling - Proficiency in Excel Ideal Skills and Experience: - Strong background in financial modeling - Familiarity with healthcare data and metrics - Advanced Excel skills, including formulas and data visualization Please provide examples of similar work done.

I need a concise 4-5 page empirical study that tracks how the EUR/USD exchange rate has moved in relation to the euro-dollar interest-rate differential. I ll provide the exact details on a pdf file.

I need assistance with cleaning and analyzing survey data for research on postpartum anxiety. Data Cleaning Tasks: - Identifying and handling missing values - Dealing with non-normally distributed data Data Analysis Tasks: - Descriptive statistics - Inferential statistics - Regression analysis Mediation analysis using PROCESS MACRO Ideal Skills & Experience: - Proficiency in statistical software (e.g., R, SPSS, MPlus) - Strong background in handling survey data - Experience with research data analysis - Knowledge of postpartum anxiety research is a plus

I need to build a complete dataset of every individual trade ever executed on sports betting markets on Polymarket, a prediction market platform running on the Polygon blockchain. The end goal is a structured file where each row represents a single trade fill, containing the wallet address, the market and event it belongs to, which sport/league it falls under, the outcome being traded, price per share, number of shares, USDC amount, timestamp, transaction hash, and whether that wallet was the maker or taker. Each row should also include the settlement result of that market (which outcome won) so that I can calculate profit and loss on my own. The dataset needs to be granular and complete enough that I can perform any analysis I want on trader behavior, performance, and patterns after deliv...

I already hold a raw-data workbook that lists each product, its department and the associated revenue, plus a separate sheet with customer details. What I need now is to turn those rows into insight while watching the entire process in real time. Here is what I want us to tackle together: • Spot revenue trends month-over-month and year-over-year. • Compare product sales by department so I can instantly see top and under-performers. • Layer in customer demographics to explain the “why” behind the numbers. We will meet on Zoom or Teams, share screen, and co-build both an Excel model (pivot tables, slicers and chart dashboards) and a Power BI report (clean data model, DAX measures, interactive visuals). I will be asking questions throughout, so please be c...

Hello, I am looking for a technical code review of a Python-based equity index construction and total return calculation engine. The project consists of: Fundamental data processing and scoring (winsorization, sector normalization, percentile filtering) Portfolio construction with multiple constraints (sector caps, regional caps, individual weight caps) Iterative weight redistribution logic Total Return engine with dividend reinvestment and divisor methodology Annual rebalance + monthly drift control Scope of work: Verify mathematical correctness of scoring and normalization. Validate weight construction logic and constraint enforcement (ensure total weight = 100% after caps and redistribution). Review Total Return calculation: dividend reinvestment divisor adjustments rebalance mechanics ...

I need a full-length research paper prepared and shepherded through publication in a Scopus-indexed Q2 journal. The topic is neural-network-based detection of visual defects in woven or knitted textiles, implemented in Python. I am flexible about the framework—TensorFlow, PyTorch, Keras or a comparable library is fine—so long as the final code is reproducible and well-commented. The paper must include a solid literature review, a clearly explained network architecture, an experimental section using a representative dataset of fabric images, and a results discussion that meets the methodological rigour typical of Q2 outlets. I will supply any proprietary images I have; if additional public datasets are needed, please curate them. Deliverables • Draft manuscript formatte...

I am preparing a full-length research article on automated fabric defect detection in industrial environments, driven by convolutional or hybrid neural networks coded in Python with TensorFlow or PyTorch. The end goal is a manuscript ready for submission to a Q2 Scopus-indexed journal, followed through peer-review until final acceptance. What I need from you • Curate or locate a high-quality, publicly shareable dataset (or assemble one from open sources) that covers common textile defects in varied lighting and weave patterns. • Design, train, and tune an appropriate neural-network architecture; document every experiment so the methodology section is fully reproducible. • Produce clear performance analyses—confusion matrices, precision-recall curves, ablation st...

I’m preparing a full-length research article that applies neural-network models, coded in Python, to detect fabric defects in an industrial setting. The goal is not only to craft a solid, data-driven manuscript but to shepherd it all the way to acceptance in a Q2-ranked Scopus journal. Scope of work The study must cover end-to-end experimentation: sourcing or curating an open or proprietary fabric-image dataset, implementing and tuning the model, analysing results against relevant baselines, and articulating the implications for real-world textile quality control. Once the research is solid, the manuscript needs structuring to meet the target journal’s author guidelines, followed by submission, peer-review revisions, and final proof corrections until the paper receives an on...

I need ten full-length practice papers for the HPRCA Hamirpur Teacher Mathematics examination, ready for upload into my app by tomorrow. Each paper must contain exactly 120 multiple-choice questions, all set at a hard level. The content mix should mirror the official syllabus issued by the board—Algebra, Calculus, Geometry, and every other area the syllabus prescribes—so that candidates experience the same spread and weightage they will face on test day. What I expect in every paper • Question text, four options, and the correct answer clearly flagged. • A concise yet complete explanation for every solution, written so a serious test-taker can understand the reasoning without further guidance. • No duplicate or near-duplicate items across the ten papers. ...

I need ten full-length practice papers for the HPRCA Hamirpur Teacher Mathematics examination, ready for upload into my app by tomorrow. Each paper must contain exactly 120 multiple-choice questions, all set at a hard level. The content mix should mirror the official syllabus issued by the board—Algebra, Calculus, Geometry, and every other area the syllabus prescribes—so that candidates experience the same spread and weightage they will face on test day. What I expect in every paper • Question text, four options, and the correct answer clearly flagged. • A concise yet complete explanation for every solution, written so a serious test-taker can understand the reasoning without further guidance. • No duplicate or near-duplicate items across the ten papers. ...

The goal is to turn long-term Reddit chatter into actionable forecasts for the equity market. Here’s the flow I need built and documented: • Data assembly   – Pull every post and comment that mentions publicly traded tickers over the past 3-5 years, using Reddit’s API (PRAW or Pushshift).   – Filter & rank tickers by daily trading volume, then lock in the top ten companies for the study.   – Store raw text, basic metadata, and a timestamp-aligned sentiment score in a clean, queryable format (Parquet or CSV). • Market reference set   – Fetch matching historical OHLCV data for those ten tickers from Yahoo Finance so each trading day can be paired with Reddit sentiment features. • Model...

I’m putting together a short-run, high-impact training series for a group of advanced Power BI users who already build reports daily and are hungry for deeper mastery. The focus is squarely on data modeling strategies and sophisticated DAX techniques that move beyond calculated columns and measures into row-level security, dynamic relationships, optimization, and real-world performance tuning. The assignment is time-critical: I’d like to roll out the first session as soon as we lock in the schedule, so please be comfortable jumping in immediately. Sessions can be live online, but recordings and reusable reference material (PBIX examples, slide deck, and answer keys to exercises) must follow each class. To keep expectations crystal clear, I’ll sign off once I can: &bul...

I will share a clean survey dataset and need a concise descriptive analysis that simply summarizes what the numbers say. Your job is to: • Run standard descriptive statistics (frequencies, means, medians, ranges). • Create easy-to-read tables and clear charts that highlight the key take-aways. • Deliver a brief written summary—plain language, no jargon—that explains the main findings so any stakeholder can grasp them quickly. Any common tool is fine; Excel, Python (pandas, matplotlib, seaborn) or R (tidyverse) all work as long as the outputs are reproducible. I’m looking for accuracy, neat formatting, and a turnaround that respects our agreed deadline.

I’m working through SAS Viya for academic purposes and need a clear, step-by-step demonstration of how to generate reports inside the platform. The focus is on data visualization, not on delivering a production-ready executive or technical document, so think of it as a teaching aid that shows — and explains — best practices. I Will need someone to share 2 hours to teach me about basic, cleansing, visualisation and creating flow What I need from you: • A sample dataset (or instructions to load an open dataset) suited to illustrating charts, graphs, and interactive visuals. • A concise walkthrough that covers the full workflow in SAS Viya: bringing data into Visual Analytics, building visual objects, arranging them on a report canvas, and publishing or export...

I have several Excel spreadsheets that hold our company’s raw financial records, and I need a clear, actionable picture of how we are performing. The core focus is on revenue- and profit-related metrics (sales volumes, margins, growth rates, month-over-month comparisons, year-to-date figures, etc.). I will supply the workbooks exactly as they stand; your job is to turn those rows and columns into insight. The process I have in mind starts with cleaning and structuring the sheets so formulas, pivot tables, or a preferred analytics script (Python / Pandas, R, Power Query—whatever you are comfortable with) can run without errors. Once the data is solid, I’d like to see: • A concise summary of key revenue and profit indicators, spotlighting any spikes, dips, or anomali...

I need a microbiologist who is formally trained in clinical microbiology and comfortable stepping beyond the bench when required. Your core responsibility will be to run targeted lab tests on our microbial strains, generate concise data sets, and translate those findings into clear, persuasive copy that positions our new biofertilizer product accurately and compellingly. In practice you will: • Carry out standard and advanced clinical-grade assays to verify strain purity, safety, and viability. • Interpret raw results, perform statistical data analysis, and prepare a brief technical report that can pass regulatory scrutiny. • distill the key benefits into marketing language—think web page blurbs, brochure text, and short social-media snippets—so non-scienti...

I'm looking for a skilled data analyst to identify trends from our database. The data includes sales, customer, and market research data. Key Requirements: - Analyze data from a database - Identify and interpret key trends - Generate insights to guide business decisions Ideal Skills: - Proficiency in SQL and data visualization tools - Experience with trend analysis - Strong analytical and reporting skills Please provide examples of similar work done.

I'm seeking an experienced math tutor for my 4th grader. The focus will be on: - Addition and subtraction - Multiplication and division - Fractions and decimals Requirements: - Tutor needed twice a week - In-person sessions preferred Ideal Skills and Experience: - Strong background in elementary math - Previous tutoring experience, especially with grade 4 - Patience and ability to engage young learners Please share your qualifications and approach.

I'm seeking an Excel expert to help me analyze customer feedback data using descriptive analysis techniques. The goal is to derive insights on customer satisfaction levels. Key tasks include: - Analyzing pre-defined customer feedback data sets. - Using Excel to perform descriptive analysis. - Visualizing data using various techniques. - Interpreting data to derive insights on customer satisfaction. Ideal candidates should possess: - Proficiency in Excel. - Experience in data analysis. - Familiarity with data visualization techniques. - Ability to interpret and derive insights from data.

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.

I need a comprehensive benchmarking study that maps out which patient-experience roles a multi-hospital group should maintain, exactly what KPIs each role owns, and how those metrics stack up against recognised best-in-class hospitals worldwide. The finished work should give me: • A clear description of each role (title, core purpose, daily responsibilities) as practised in leading hospitals. • A justified KPI set for every role, showing precise definitions, formulas and recommended targets. • Side-by-side comparison of our current structure and metrics versus benchmark organisations, highlighting performance gaps. • Practical recommendations on governance—who measures, who reports, and how results cascade through the organisation. Please base the an...

I’m putting together a complete video course in Hindi and English that guides absolute beginners through the full journey of data analysis—from first principles all the way to hands-on work with popular tools such as Excel and Tableau. I need you to record the lessons yourself, speaking clearly, sharing your screen, and demonstrating every step so viewers can follow along in real time. The flow should start with fundamental concepts—types of data, descriptive statistics, basic visualisations—and gradually move into more advanced techniques like pivot tables, forecasting, and dashboard creation. Practical, example-driven teaching is essential; the audience has no prior experience, so every technique must be shown in context with a downloadable dataset. Deliverables...

I have an intermediate-level assignment that must be completed in Excel with the @Risk add-in, and I want to finish it myself while being coached in real time. My main sticking points are building the simulations correctly and interpreting the risk analysis output that follows, so I’ll need you to explain each step, verify my formulas, and help me understand the Monte Carlo results rather than simply doing the work for me. Speed is important—I’m ready to start as soon as you are and would like to wrap this up quickly. Because this is a walkthrough, live collaboration (screen-share or similar) is essential. I’m comfortable scheduling multiple short sessions if that’s easier, but I’d like clear milestones so I always know what comes next and can practise ...

I'm looking for an expert to analyze risks using @RISK an excel addon. Key Requirements: - Proficiency in @RISK - Experience with risk analysis using @Risk - Ability to interpret and analyze complex data sets would like to jump on a call with and take me through the whole process rather than just doing it from their end.

Assalamu alaikum! Are you looking to better understand financial markets without the hype or false promises? I'm here to provide clear, detailed, and educational analysis based on years of studying and mastering technical, fundamental, and psychological aspects of trading. The market is psychological warfare – a constant battle of emotions where fear, greed, FOMO, and manipulation by large players drive price action more than pure logic. Most losses come not from bad charts, but from failing to win the inner war against your own mind and the crowd's psychology. I help you navigate this battlefield with discipline and insight. What I offer: Technical Analysis: Chart markups, key patterns (head & shoulders, flags, triangles, double tops/bottoms), support/resistance leve...

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...

I have a collection of datasets that need to be explored from every angle. First, I want a clear descriptive snapshot that tells me what is happening in the data right now. From there, I need predictive models that forecast future trends, and finally prescriptive recommendations that translate those forecasts into concrete, data-driven actions. You are free to move between Excel pivot tables, Python (preferably pandas, scikit-learn, and matplotlib or seaborn), and R (tidyverse, ggplot2, caret) as each step requires. The end goal is a versatile analysis that can power business decisions, support an academic write-up, and improve day-to-day operational efficiency. Please include: • Cleaned and well-documented datasets • Reproducible Excel workbooks, Python scripts or notebo...

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 AI agent in Copilot to analyze Excel spreadsheets. The spreadsheet shows monitoring visit compliance. The agent should be able to determine if a visit has been compliant within the allowable visit window. Ideal Skills: - Experience with AI and machine learning - Proficiency in Excel, especially in data analysis - Strong programming skills (Python, R, etc.) - Familiarity with data visualization tools

I need a Power BI dashboard for leadership review. The primary focus is to visualize the organization chart. Requirements: - Connect to Excel spreadsheets - Create a comprehensive organization chart Ideal Skills: - Proficiency in Power BI - Experience with Excel data integration - Strong data visualization skills

I have a collection of customer reviews that must be transformed into clear, data-driven insight. The raw files might arrive as CSV, Excel, or even straight from a database—the format is flexible—so the first task is to clean and standardise whatever I supply. That means handling empty rows, removing noise (HTML tags, punctuation, stop-words, etc.) and normalising the text. Once the data is tidy I need robust sentiment classification. Please build the pipeline in Python, making sensible use of NLTK and/or TextBlob for tokenisation, lemmatisation and polarity scoring. The reviews span more than one language, but the immediate focus is on the English subset; your code should therefore detect language and process only English for this milestone while staying extensible for future...

I have a collection of customer reviews that must be transformed into clear, data-driven insight. The raw files might arrive as CSV, Excel, or even straight from a database—the format is flexible—so the first task is to clean and standardise whatever I supply. That means handling empty rows, removing noise (HTML tags, punctuation, stop-words, etc.) and normalising the text. Once the data is tidy I need robust sentiment classification. Please build the pipeline in Python, making sensible use of NLTK and/or TextBlob for tokenisation, lemmatisation and polarity scoring. The reviews span more than one language, but the immediate focus is on the English subset; your code should therefore detect language and process only English for this milestone while staying extensible for future...

I need help bringing together a batch of mixed data—both text and numbers—into one clean, well-structured file. The numerical portion already lives in several Excel spreadsheets, while the text accompanies each record in separate digital files that I will supply. Your task is to copy-paste or re-key these details into the template I provide, double-checking that every field lines up correctly and that numeric values remain exactly as stored in the original sheets. Accuracy is more important to me than speed, but I still need the work turned around promptly. Please be comfortable navigating Excel, using basic formulas to validate totals where needed, and spotting inconsistencies such as misplaced decimals or stray characters in the text. Deliverables • A single, consoli...

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...

I am coordinating a large-scale healthcare randomised controlled trial and, now that we are midway through data collection, I need an experienced biostatistics partner who can carry the project through to publication and simultaneously prepare a systematic review on the same topic. For the RCT you will take over live clinical-trial data streams, refine the data collection and management workflow, perform all required statistical analyses, then translate the findings into a clear manuscript-ready report and slide deck. Because the trial is already registered and governed by strict SOPs and GDPR, familiarity with GCP, REDCap (or similar), and reproducible R scripts/SAS code is essential. Alongside the trial work I also need a full systematic review following PRISMA guidelines. You will han...

I have a set of time-stamped observations and I need a robust machine-learning solution that can forecast future values with solid accuracy. The end goal is an automated prediction/forecasting model that I can retrain as new data arrives and easily integrate into a larger Python pipeline. Here’s what I need from you: • Exploratory analysis of the raw time-series data, spotting seasonality, trends, and anomalies. • Thoughtful feature engineering (lags, rolling stats, calendar effects, exogenous variables if useful). • Model selection and training – I’m open to traditional approaches such as ARIMA/Prophet as well as more advanced architectures like Gradient Boosting or LSTM; choose what performs best and explain why. • Rigorous evaluation on a ho...

I need to turn raw treasury-trading deal data into clear, decision-ready performance reports. The core of the job is to build a repeatable process that reads my daily deal files, analyses them, and produces a set of Performance Reports covering three key metrics: • Return on Investment • Trading Volume • Profit & Loss Statement . RATES AND MORE The source files arrive in CSV/Excel straight from our treasury platform. I am comfortable sharing a sample dataset so you can map the fields, clean anomalies, and transform the numbers. Ideally the workflow is automated—SQL or Python for the heavy lifting and Excel, Power BI or Tableau for the final dashboards and printable summaries—but I am open to whichever stack you can justify as robust and maintainable....