HLT-362V: Applied Statistics for Health Care Professionals is an introductory course on concepts of statistics, emphasizing applications to health care professions. The course is designed to prepare learners to understand concepts of statistics and the appropriateness of statistical methods used in published research papers and a variety of settings. Areas of emphasis include an introduction to the statistical analysis concepts of variable/reliability factors; P values; experimental design; descriptive statistics, including mean, median, and mode; sampling methods; and power analysis.
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What is Applied Statistics?
Applied Statistics includes planning for the collection of data, managing data, analyzing, interpreting, and drawing conclusions from data, and identifying problems, solutions, and opportunities using the analysis.
HLT-362V: Applied Statistics for Health Care Professionals unit is a major course from the health science discipline. It focuses on various concepts of statistics and emphasizing applications for health care professionals. Moreover, this course allows the study of learning the basic concepts of statistics and their appropriateness for different kinds of settings. Additionally, it also includes the study of different factors and courses such as reliability factors and statistical analysis concepts for variable and experimental designs based on descriptive statistics such as mean, mode, median and sampling methods, and power analysis.
With our HLT-362V: Applied Statistics for Health Care Professionals course assignment help, we will help you to build critical thinking and problem-solving skills in data analysis and empirical research.
Learning outcomes of studying HLT-362V: Applied Statistics for Health Care Professionals unit.
- The student is able to demonstrate an understanding of statistical techniques widely used to conduct healthcare research
- The learner can develop a study design to appropriately address a research question
- You are able to differentiate between the various components in a statistical model (variables, parameters, error)
- You are able to calculate the performance characteristics of a clinical assay (sensitivity, specificity, predictive value)
- The learner is able to conduct a simple analysis of [at least] three variables (predictor, outcome and other) using statistical software.