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Course Overview

The course is organized to give you a solid foundation in health research methods with either a focus on applied statistics or a more general overview of health research methodology. It will provide you with opportunities to develop your knowledge in the field and build your applied statistical skills, knowledge of health research methodology, and scientific writing skills.

This course will teach you the core building blocks of statistical analysis – types of variables, common distributions, hypothesis testing – but, more than that, it will enable you to take a data set you’ve never seen before, describe its keys features, get to know its strengths and quirks, run some vital basic analyses and then formulate and test hypotheses based on means and proportions. You’ll then have a solid grounding to move on to more sophisticated analysis.

This course will introduce you to some of the key building blocks of knowledge in statistical analysis: types of variables, common distributions, and sampling. You’ll see the difference between “well-behaved” data distributions, such as the normal and the Poisson, and real-world ones that are common in public health data sets.

Course Objective

By the end of the program, delegates will be able to:

  • Define research methodologies to successfully conduct research studies
  • Describe and compare major quantitative and qualitative research methods
  • Successfully implement research studies within the organization
  • Apply biostatistics in public health and biomedical researches
  • Assess data sources and data quality for the purpose of selecting appropriate data for specific research questions
  • Translate research objectives into clear, testable statistical hypotheses
  • Describe basic principles and the practical importance of key biostatistics concepts
  • Apply numerical, tabular, and graphical descriptive techniques to characterize and summarize public health data

Training Methodology

The Training methodology consists of face-to-face interactions, presentations, case studies and workgroups, Individual and Group experiential learning activities, Practicals, Audio/Video presentations, and Questionnaire, are the forms in which the training will be delivered.

Like all of our courses, it follows our Do-Review-Learn-Apply Model.

Who Should Attend

Healthcare researchers, strategists, planners, administrators, VP and C-suite executives, chiefs of staff, hospital board members, chief nursing officers, department directors, and other healthcare professionals with management responsibility.

This course would also benefit clinicians, medical personnel, and staff who are transitioning upward into administrative, management, director, or executive leadership roles.

Course Outline

Module 1 – HEALTH ECONOMICS AND RESEARCH

  • Markets and market failure for health and health care
  • Identifying, measuring, and valuing costs
  • Measuring consequences in an economic evaluation
  • Sources of Health Economic Data
  • Decision tree Models and Markov Models
  • Writing protocols

Module 2 – STATISTICS IN PUBLIC HEALTH

  • Health Research Methods
  • Collecting Data
  • Analyzing Data
  • Study designs
  • Observational studies
  • Randomized controlled trials
  • Systematic reviews & meta-analysis

Module 3 – MEASUREMENT IN HEALTH & DISEASE

  • Measurement Error
  • Observer Variation
  • Limits of Agreement
  • Composite Scales and Scores
  • Diagnostic Tests
  • The validity of measurement instruments

Module 4 – EPIDEMIOLOGY STATISTICS

  • Indices of health and disease
  • Data sources and collection
  • Study types and design, and their limitations
  • Measures of association, their calculation, and interpretation
  • Assessment of cause and effect, confounding and bias

Module 5 – BASICS OF BIOSTATISTICS

  • Descriptive statistics
  • Probabilities
  • Probability distributions
  • Sampling distributions
  • Estimations
  • Hypothesis testing
  • Analysis of variance
  • Simple linear regression and correlation
  • Multiple regression and correlations
  • Chi-square distribution
  • Non-parametric and distribution-free statistics
  • Survival analysis

Module 6 – STATISTICAL DATA COLLECTION AND RESEARCH TOOLS

  • Sources of Data – Primary and Secondary Data
  • Sampling during data collection
  • Qualitative research data collection
  • Quantitative research data collection
  • Participatory data collection methods
  • Introduction to data triangulation

Module 7 – DESCRIPTIVE DATA RESEARCH: SURVEYS & ANALYTICS

  • Parts of a Survey
  • Open-Ended/Closed-Ended Questions
  • Levels of Measurement
  • Determining Scales
  • Sources of Possible Survey Error
  • Increasing the Response Rate
  • Electronic Survey Tools
  • Survey Design
  • Passive Data Collection
  • Media Planning

Module 8 – QUALITATIVE & QUANTITATIVE DATA ANALYSIS

  • Data preparation for qualitative analysis
  • Thematic analysis for qualitative data
  • Content analysis for qualitative data
  • Creating variables and data entry
  • Data reconstruction
  • Understanding data weighting
  • Inferential statistics: hypothesis testing, regression analysis
  • Manipulation and analysis of data

 

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Customized Schedule is available for all courses irrespective of dates on the Calendar. Please get in touch with us for details.

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