Video Academy | Sanitary area
The statistical analysis techniques presented in these videos are applicable to all thematic areas, focusing specifically onexamplesof typehealth doctor,scientificandepidemiological.
Statistics for Data Analysis Vs Excel
In this video, we will compare Statistics for Data Analysis powered by SPSS against traditional Excel, showing you the significant advantages the statistical package offers, including:
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Mastering Complex Tests: gain immediate access to advanced statistical tests (like Regression and ANOVA) and complex models.
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Guaranteed Methodological Reliability: trust your results! Pre-validated formulas.
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Analyzing Large Data: handle huge datasets without any loss of quality or performance.
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Precise Date Calculations: accurately manage and compute complex date-related variables.
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Clear Data Visualization: create insightful data visualizations and generate effective reports with just a few clicks.
The Survival Curve
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In this video, we'll demonstrate how to apply one of the most critical statistical tools used in medical and scientific research: the Survival Curve.
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You'll discover how to analyze and interpret survival data (or the time elapsed until a specific event occurs).
Furthermore, you'll learn how to compare one or more survival curves to draw statistically significant conclusions.
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The Value of Data
Always remember: raw data has no intrinsic value.
It is only through proper management and analysis that we can transform it into actionable information for three fundamental goals: making better decisions, improving operational efficiency, and increasing competitiveness.
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In this video, we will explore a series of fundamental topics essential for mastering data management and effective analysis.
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Anova with Statistics for Data Analysis
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As understand the effectivenessof a new drug?
We will have two groups of patients: one has been given the new treatment, while the other has been given the existing substance.
Discover the technique ofAnalysis of Variance (ANOVA) watching the video.
After an initial theoretical overview, we will build and interpret the data with the Statistics for Data Analysis solution, powered by IBM SPSS.
Subjects:
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Introductory contextat the ANOVA
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Features andhiring
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Practical examplewith Statistics for Data Analysis
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Find out what you can do with the form Basic
The impact of data on the digitization of healthcare:
the GVM case
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Webinar dedicated to the collaboration with ourGVM customer historyCare&Research, in which we explore the theme ofimpactthat thedatahave on the entire healthcare sector, from care, toresearch, up togovernance.
Together with Maria Avolio, Head of the GVM Clinical Data Analysis Unit, we will show some practical examples withStatistics for Data Analysissolution that includes SPSS, and that is bysupportacross the board aall areas of health care.
In particular, we will be able to show the simplicity, practicality and speed of use for the purposes of:
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AssistanceAndtreatmentimproving clinical performance
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Research, enhancing the data also coming from small healthcare facilities,
not only those of the large university polyclinics -
Government of structures, providing the tools to understand where to invest and where to save
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Look at the features Basic module ​
The Chi-Square Test
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The Chi-square test is one of the most common and simple tests of statistical significance, it is widely used in any type of experiment, from biology to medicine, from chemistry to environmental and social sciences.
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Subjects:
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Measuresof statistical association for categorical data
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Chi-square ofpearson
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Chi-square analysis for paired data: theMcNemar test
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Practical exampleon a data set of patients who underwent astroke event and related intervention.
The Chi-squared test is found inBasic module ​
How to choose a Statistical Test?
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When statistical analyzes have as a starting pointsample data, of fundamental importance are thestatistical teststoextendthe results to a larger population.
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How to orient yourself inchoice of statistical testmost appropriate, to maximize the likelihood of putting inevidencea certaineffectand understand if it is actually present in the population?
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Subjects:
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Testparametric
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Testnon-parametric
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Comparisonbetween parametric and non-parametric tests
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Look at the features Basic module
Data preparation with Statistics for Data Analysis
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During this presentation we show the use of the Data and Transform menus dedicated todata preparation, a necessary phase to improve its quality before its use in the analysis phases.
Data cleaning and transformation are essential to be able to guarantee whoever doesresearchAndEducationobtaining reliable and accurate results.
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Subjects:
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Renovationsome data
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Aggregationof data
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Recodeof variables
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Calculationof new variables
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Rulesdata validation
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Practical examplerelating to asurvey of patients treated with an anxiolytic
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look at the characteristics of Data Preparation module
Health surveillance of emission sources with potential impact on the territory
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During this webinar we talk about the fundamental role of Statistics for Data Analysis in thedata analysiscoming from polluting sources, which can be the direct and indirect cause ofhealth effects on the population.
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Dr. Gaia Fallani, collaborator of the Public Health Department of the Parma Local Health Authority, will show usspecific cases,analyzingsample data frommonitoringboth onterritoryboth onpopulation, with particular attention tosubjectswhich:
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Statisticsexploratory
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Normalitydistributive
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Testparametric
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Testnon-parametric
Data analysis for screening programs
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This presentation aims to show you acase studieson the use of Statistics for Data Analysis in the medical and healthcare fields, where you will be able to see andconcrete examples, which will exploit the professionalism and ease of use of the tool to:
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Preparethe data for analysis
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Managemultiple choice data
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Identifyautomatically duplicate cases
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Aggregatethe data
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Individuatethe target patients for the analysis
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To analyzethe output of the results
Introduction to data analysis for research
scientific and medical
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During this presentation we show an overview of themain statistical techniquesused in scientific research, capable ofto commutethe data intoinformationuseful andunderstandable, highlighting the irregularities and verifying the statistical hypotheses.
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The aim is to highlight the professionalism combined with the ease of use of Statistics for Data Analysis through the use of practical examples.
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Subjects:
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Descriptive statistics​
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Normal curve
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InferenceStatistics​
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Hints atlinear and logistic models​
Look at the features Basic module
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Data analysis with Statistics for Data Analysis on data from doctor visits and patients
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This webinar aims to present thecase studytypicalrequested by the top management of a healthcare company, for the analysis aimed at understanding and interpreting the data, transforming it into useful information.
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The study is based on data from adatabaseOfspecialist servicesto registered patients on a per-visit basis.
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Through the use of Statistics for Data Analysis, we will be able toto explorethe database, ofpreparedata for analysis, up to airesultsof the study, which will allow us todistinguishbetween the number of visits and patients and the types of patients who received a given therapy.
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