Global Certificate in Quantitative Health Data Analysis
-- ViewingNowThe Global Certificate in Quantitative Health Data Analysis is a comprehensive course designed to equip learners with essential skills in health data analysis. This certification is crucial in today's data-driven world, where the healthcare industry is increasingly relying on quantitative data to make informed decisions.
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⢠Introduction to Quantitative Health Data Analysis: Defining key terms, exploring data types, and understanding the fundamentals of quantitative analysis in health care.
⢠Data Collection Methods: Surveys, experiments, and observational studies; understanding the strengths and weaknesses of various data collection methods in quantitative health analysis.
⢠Data Cleaning and Preparation: Identifying and handling missing data, outliers, and inconsistencies for accurate analysis.
⢠Descriptive Statistics: Measures of central tendency, dispersion, and association; understanding how to calculate and interpret these measures.
⢠Inferential Statistics: Hypothesis testing, confidence intervals, and p-values; learning how to make inferences and predictions based on data.
⢠Regression Analysis: Simple and multiple linear regression, logistic regression, and other regression techniques for modeling relationships between variables.
⢠Analysis of Variance (ANOVA): Understanding the principles and applications of ANOVA for comparing the means of multiple groups.
⢠Nonparametric Tests: Learning alternative statistical tests for non-normally distributed data or small sample sizes.
⢠Data Visualization: Creating effective charts, graphs, and tables to communicate quantitative health data insights.
⢠Ethics and Bias in Quantitative Health Data Analysis: Exploring ethical considerations, potential biases, and responsible reporting practices.
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