SPSS Statistics Jobs

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'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.

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.

I have a working Python script that already tackles a portion of my scientific-data analysis, but it needs a full refresh so it can: • clean and preprocess raw experimental files (handling missing values, unit conversions, outlier checks) • run the required statistical analyses (descriptive stats, hypothesis testing, regression where relevant) • generate clear, publication-quality visualisations of the results The current code is organised in a single file. I want it refactored into well-named functions or classes, documented with concise docstrings, and wrapped in a short Jupyter notebook that demonstrates the new workflow from import to final figure. Please keep any existing logic that is still valid but feel free to streamline it with modern libraries—panda...

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...

We are looking for a skilled professional with strong experience in healthcare data systems and data modeling concepts. The ideal candidate should have hands-on experience working with Electronic Health Records (EHR) data and a good understanding of clinical and Revenue Cycle Management (RCM) domains within hospital systems. Key Responsibilities •⁠ ⁠Work with healthcare data from leading EHR platforms such as EPIC, Oracle Cerner, MEDITECH, or other top-tier EHR systems. •⁠ ⁠Understand and model clinical and RCM entities, including relationships within hospital and healthcare ecosystems. •⁠ ⁠Apply Kimball modeling techniques and core data modeling concepts for analytics and reporting solutions. •⁠ ⁠Support data integration, transformation, and structuring for health...

We are looking for an experienced researcher or data analyst with strong knowledge of Confirmatory Factor Analysis (CFA) to assist with an academic thesis task. The project relates to the following Topic: What are the key influencing mechanisms of South African women's self-undermining and labyrinthine paths to attaining their first promotion? Scope of Work: Perform Confirmatory Factor Analysis (CFA) on the provided dataset. The data is already cleaned and Exploratory Factor Analysis (EFA) has been completed in SPSS. Your task is to test the measurement instrument items, identify low-loading items, eliminate them, and retain the high-loading items. Develop the Results and Discussion section (approx. 2000 words) based on the CFA findings. Follow the format and guidance from a jo...

I’m looking for a seasoned researcher

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’m running several data-science driven market research projects and need a sharp management trainee who can keep the wheels turning while digging deep into consumer behaviour. Your main focus will be consumer research—specifically behavioural patterns—so expect to be involved in everything from shaping survey instruments and sourcing secondary data to translating raw numbers into clear, decision-ready narratives for stakeholders. Day-to-day you’ll help me: • Coordinate timelines, milestones, and cross-functional touch-points so each study stays on track. • Collect and clean behavioural data, whether it comes from surveys, web analytics, or CRM exports. • Perform exploratory analysis in Excel, Python, R or any tool you prefer, then visualise ke...

I have a set of raw sales data that I need turned into clear, actionable insights. The files are ready for you to dive in, and I’m looking for someone who can clean, explore, and analyze the numbers, then present the key findings in a way that guides smarter decisions. Please outline how you would approach the analysis—methods, preferred tools (Python / R, Excel, Tableau, Power BI, etc.), and what kinds of visualizations or reports you typically deliver. If you see opportunities for deeper trend identification or forecasting, feel free to suggest them; I welcome recommendations that add value. At the end, I’ll need: • A concise report summarizing your findings and recommendations • Supporting dashboards or charts that make the results easy to grasp •...

Headline: Driving Decisions with Data: The BMW Sales Analytics Dashboard Luxury brands don't just sell products; they sell experiences. But behind every premium experience is a massive engine of data. I’ve built a comprehensive BMW Sales Dashboard in Power BI to analyze how one of the world’s most iconic automotive brands performs across different markets. This project isn't just about the "Ultimate Driving Machine"—it’s about the Ultimate Data Insights. Key Insights Captured: Model Performance: Identifying which series (3 Series, X5, i7) is leading the revenue charts. Regional Deep-Dive: Mapping sales distribution across global territories to spot emerging markets. Engine Type Trends: Analyzing the shift from traditional Internal Combustio...

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...