Empowering Data Insights
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Expert Statistical Analysis
Dedicated to simplifying statistical analysis, igniting a passion for data visualization, and empowering clients to make informed decisions. Our mission is to provide top-notch statistical analysis and data visualization services that are easily understandable and actionable. At STATSENSE, LLC, we strive to offer high-quality solutions tailored to meet the unique needs of each client. With a focus on accuracy, efficiency, and innovation, we are committed to helping our clients unlock the power of their data.
Services
Industrial SPC
Statistical Process Control is an invaluable way to monitor your process, spot trends before they become problems, and determine process capability. It ensures the process is operating optimally and efficiently. It is a tool that separates real problems from normal process variation. Implementing SPC in your business reduces rework and scrap, decreases cost, maximizes productivity, and increases customer satisfaction.
Custom Statistical Analysis
A picture is worth a thousand words and most often it's the first place to start in data analysis. We can provide graphs such as bar charts, histograms, Pareto charts, run charts, and more. Statistical analysis methods used include but not limited to regression analysis, sampling plan creation, probability analysis, forecasting, time series analysis, and more. We'll tailor the statistical analysis to fit your specific needs.
Industrial Research (DOE)
Design of experiments (DOE) is an efficient method to study the relationship between multiple input variables and output variables. Design of experiments are used to determine optimal variable settings that minimize variation and improve efficiency. Industrial screening designs are a useful tool to reduce the number of process variables quickly and efficiently to determine the ones most important to process quality and output.
Waste Management Sector
Statistical methods are used to analyze waste composition, identify different materials, and understand waste patterns. This analysis can identify correlations between different waste types. Descriptive statistics are used to summarize and characterize waste data. Leveraging inferential statistics is very useful to draw conclusions about larger populations based on sample data. Create statistical sampling schemes using methods such as simple random sampling, stratified sampling, cluster sampling, and systematic sampling to collect environmental data.