Biostats introduction lecture on biostatistics for advance studies
- 3. Topic: Introduction to Biostatistics Course: Biostatistics Tahira Ashraf (Senior Lecturer, Biostatistics) (University of Lahore)
- 4. STATISTICS Statistics is defined as: • Study of facts and figures • Deals with collection, organization, analysis and interpretation of numerical data
- 5. Why we use Statistics How many males and females are present here? What is the mortality rate of Pakistan? What is the proportion of male to female students who failed every year in metric? What is risk to develop Lung Cancer for those who are smokers? To give answers of our daily lives problems
- 6. Bio-Statistics “Bio” means life. “Statistics” Science of facts and figures
- 7. DEFINITION • It is the branch of statistics that concerns with the applications of statistical methods to medical and biological data. • Biostatisticians turn health data into knowledge
- 8. WHY WE NEED BIOSTATISTICS • Biostatistics is integral to the advancement of knowledge • Has imperative part in public health policy making • Important role in research related to field of biology, health policy, clinical medicine, health economics, genomics, proteomics, and many others
- 9. WHO DOES THE JOB
- 10. BIOSTATISTICIANS
- 11. WHAT DO THEY DO?
- 12. WHAT BIOSTATISTICIANS DO • Biostatisticians are the “ the specialists of data evaluation” • They have expertise that allows them to take complex, mathematical findings of clinical trials and research-related data and translate them into valuable information that is used to make public health decisions.
- 13. WHAT BIOSTATISTICIANS DO • Designing and conducting experiments related to health, emergency management, and safety • Collecting and analyzing data to improve current public health programs and identify problems and solutions in the public health sector • Interpreting the results of their findings
- 14. WHAT BIOSTATISTICIANS DO • Help answer pressing research questions in medicine, biology and public health • To make sense of different sources of variation and rationalize this • Make valid inferences that can be used to solve problems in public health
- 16. Variables & Constants Age Weight Height Severity of Pain Salary Value of “g” Value of “pai” Variables: A characteristic that varies from individual to individual or subject to subject Constants: That remains same from person to person or place to place
- 17. VARIABLE • DEFINITION: A characteristic or attribute that varies from individual to individual is termed as variable. • EXAMPLE: Gender, Age, Severity of disease, Disease status, BMI etc.
- 18. CONSTANT • DEFINITION: A characteristic or attribute that does not change from individual to individual in a particular study • EXAMPLE: The gender in study title “Incidence of Low Back Pain (LBP) among female students of UOL” will be constant
- 19. CHOOSE VARIABLE VS CONSTANT 1. MATERNAL GENDER 2. NEWBORN GENDER 3. MATERNAL AGE “ Association of maternal anemia with preterm birth”
- 20. 1. GENDER 2. AGE “ Risk factors of IHD in patients visiting OPD of PIC Lahore” CHOOSE VARIABLE VS CONSTANT
- 21. CHOOSE VARIABLE VS CONSTANT 1. GENDER 2. DISEASE STATUS “ Signs and symptoms of young female patients of Acne Vulgaris”
- 23. Types of Variables in Research Independent Variables The variable used to describe or measure the factors that are assumed to cause or at least to influence the problem Example Drug vs placebo Gender and age
- 24. Types of Variables in Research Dependent Variables The variable that gets modified under the influence of some other variable (independent) Examples Smoking causes lung cancer Physical inactivity causes heart problems Exposure to radiations cause cancer
- 25. EXAMPLES Smoking causes lung cancer Physical inactivity causes heart problems Exposure to radiations cause cancer INDEPENDENT DEPENDENT
- 26. AND THE PROBLEMATIC ONE THE CONFIUNDING VARIABLE
- 27. Types of Variables in Research Confounding Variables that effects both the independent and dependent variables and thus confuse the result • Disturbs the relationship between independent and dependent variable • Effects the authenticity of research • Needs to be eliminated or controlled
- 28. For Example Cause Effect/ outcome Independent variable Dependent variable Other Factors (Confounding Variables)
- 29. For Example A relationship is shown between the low level of mother’s education and malnutrition in under 5’s. However, family income may be related to the mother’s education as well as to malnutrition Mother’s Education Malnutrition Independent variable Dependent variable Family Income (Confounding Variables)
- 30. MORE EXAMPLES Physical Activity Myocardial Infarction Age
- 31. MORE EXAMPLES Fertilizer X Plant growth Rain
- 32. THANK YOU