Inhalt: Data curation is quickly evolving as a required skill and job function in data teams and organizations. Creating and sharing data curation files can help you more efficiently and effectively manage the work of teams, and leverage their data for analytics and decision-making. In this course, Monika Wahi demonstrates how to develop curation files to document information about datasets and related business processes. Monika provides an overview of five categories of data curation files: files for back-end curation, different files for front-end curation, survey curation files, flow diagrams, and text-based curation files. She goes over a variety of curation files from each category, providing guidance as to how to develop them using Microsoft Word, Excel, or PowerPoint. Umfang: 04:56:20.00
Inhalt: Analyze behavior and risk using R, the open-source statistical computing software. R provides an environment and a language you can use to analyze data, including the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset. This course teaches core healthcare data science skills, including epidemiology, as well as how to perform a cross-sectional analysis, set up a data dictionary, develop metadata, determine confounders, apply exclusions, create diagrams, generate continuous and categorical outcome variables, and more. Join biotech expert and epidemiologist Monika Wahi as she first discusses design and ethical considerations, and then takes you through the steps of conducting a descriptive analysis. This detailed, practical course is designed to help those in the field of public health, medicine, and data science to edit, analyze, and interpret data. Learn how to code new variables, use the forward-stepwise modeling process, and document your decisions. Find out how to visualize results by generating charts and graphics, and how to add tables and figures to your documentation. This course helps equip you to independently design, develop, and execute a full BRFSS analysis, and even publish your results in scientific publications or journals. Umfang: 04:15:43.00
Inhalt: Even if you have a strong grasp of statistics and informatics, you also need to understand epidemiology and basic study design to perform accurate, rigorous analysis of healthcare data. This course will help you design research studies around hypotheses, and fill the knowledge gap that many of today's analysts face when entering the healthcare field. Instructor Monika Wahi defines basic terms and concepts in epidemiology, and reviews the different study design approaches: descriptive, analytic, cross-sectional, and case control. She dives into detail on cross-sectional and case-control studies, and shows how to plan an analytic data set: figuring out the necessary native variables and operationalizing them in a data dictionary. Last, she reviews the lessons learned from the course and prepares you for part two of the training series, which tackles the descriptive and regression analysis for the data set you have designed. Umfang: 02:15:24.00
Inhalt: To perform accurate healthcare data analysis, you need to understand epidemiology and basic study design-covered in part one of this training series. But you also have to be able to conduct descriptive and regression analysis and defend your decisions regarding model selection, interpretation, and presentation. Part two of our series on Designing Big Data Healthcare Studies covers the logistics of planning and executing analysis on the analytic data set prepared in the previous course. Instructor Monika Wahi shows how to conduct the analysis and interpret the final model in context of your original hypothesis. Along the way, she teaches about best practices for code naming and arrangement, stepwise selection modeling, odd and prevalence ratios, and relative risk. Using these tutorials, you should be able to design great healthcare studies that take advantage of all that big data has to offer. Umfang: 01:35:25.00
Inhalt: Linear and logistic regression models can be created using R, the open-source statistical computing software. In this course, biotech expert and epidemiologist Monika Wahi uses the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset to show you how to perform a forward stepwise modeling process. Monika shows you how to design your research by considering scientific plausibility selecting a hypothesis. Then, she takes you through the steps of preparing, developing, and finalizing both a linear regression model and a logistic regression model. She also shares techniques for how to interpret diagnostic plots, improve model fit, compare models, and more. Umfang: 04:02:06.00
Inhalt: After literally decades on the scene, SAS is still an industry leader in the world of big data. If healthcare analytics piques your interest-and you want to get up and running with this venerable data analytics platform-then this course is for you. Join instructor Monika Wahi as she steps through how to conduct a descriptive analysis of a health survey dataset and present the results in plots and tables. Monika covers how to import a dataset from SAS *.xpt format using the XPORT command; edit datasets to add new categorical and continuous variables; conduct chi-square tests, t-tests, and analyses of variance (ANOVAs); generate a descriptive analysis with either a categorical and a continuous dependent variable; and more. Umfang: 04:07:22.00
Inhalt: SAS is a venerable data analytics platform that boasts millions of users worldwide and a slew of useful features. In this course, instructor Monika Wahi helps you deepen your SAS knowledge by showing how to use the platform to conduct a regression analysis of a health survey data center. Throughout the course, Monika demonstrates how to conduct regression analyses and present your model results in tables. She shows how to develop and present a linear regression model using PROC GLM as part of a hypothesis-driven analysis; how to do a logistic regression model in both PROC GENMOD and PROC LOGISTIC; and how to present and interpret your linear and logistic regression models. To wrap up, she goes over issues in regression and provides a few helpful tips. Umfang: 03:30:18.00
Inhalt: Interested in learning how to create an online experiment that helps you better understand your business? This course can help you get up to speed. Instructor Monika Wahi shows learners without a background in experimental design how to build an A/B test for a web page, run the test, analyze the data, and make decisions based on the results of the test. Monika begins by explaining exactly what A/B testing is and under what circumstances it is useful. She then covers potential strategies for increasing conversion rates, as well as how to choose both A and B conditions for testing. Next, she explains how to define conversion rates and develop and document case definitions, conduct a baseline analysis in Excel and, based on the results of the analysis, design an A/B test. Plus, she demonstrates how to conduct a chi-square test in Excel and get a sample size estimate using G*Power. Umfang: 03:35:42.00
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