Quantitative Insights
Quantitative research produces large sets of numeric data for accurate and repeatable analysis. It is crucial to convert data into great insights, to interpret data in a more meaningful matter, and to apply the analysis results into practice. Our quantitative insights services support you to take what the data shows and determine how to use the results for effective change.
Results Presentation
What is it? Results presentation, which often includes dissemination, is all about delivering important data results to the public so that they can step towards change. Information should be conveyed in an easy and understandable manner. The presentation of results can include written reports, tables, and graphs. The purpose of the presentation, level of audience, statistical analysis methods, and the complexity of the content should always be considered when identifying what format should be used. One of the most common ways to reach a wide audience is through publishing clear, logical, and concise results in a journal (manuscript publication).
Elite Research consultants use a variety of software, such as HTML, JAVASCRIPT, Tableau, and CSS, to create visual outputs. If you are unsure about the most appropriate format for your intended purpose or are unsure how to present your results, let us help you.
How can we help you?
- Write methods and results in the manuscript
- Preparing for manuscript backbone following journal guidance
- Create static and dynamic data visualization
- Create tables and figure for date representation
- Review manuscript draft and provide comments
- Editing
- Design posters and power point presentations
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Read MoreFAQ About Results Representation
Existing reviews and studies give access to best practices, market research information and infrastructure developments with limited cost in resources and time. It is incredibly valuable to understand which reviews/studies will be profitable and applicable to portions of your operations.
Combining offline and online data collection is normally straightforward provided that the collection mechanisms are compatible. Data is often collected in a CSV or other standard formatting procedure that can be exported to Excel or another software packaging system that can be cleaned and analyzed.
Selecting the appropriate analysis depends on the nature of variables and the characteristics of those variables.
A one-sample t-test compares measured values against the mean values for known (published) or hypothesized values.
Small sample sizes will have lower statistical power. This requires a greater effect size in order to obtain significant findings. This means that if the expected difference between two different groups is not large enough, it will not result in significant findings for smaller samples in certain analyses.
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