Glossary - Research Basics and Terminology

• Proportion of a population having a particular condition at a specific point of time
• Used to look at burden of disease in a population
• Example: percentage of men over 40 with lung cancer today in Bavaria

• Probability that the statistical results occurred by chance
• When p-values is smaller than the stated level of significance (α-value), H0 is rejected 

• Number of subjects: small
  
• Type of data collection: observations, patient interviews, verbal interactions
  
• Objective: to generate hypothesis, exploratory and not conclusive
  
• Example: Physicians’ opinion about vaccination
  

• Number of subjects: large
• Type of data collection: questionnaires, counting, experimental trials
• Objective: to test a hypothesis, used to recommend course of action
• Example: Mean time youths spend with their mobile devices a day

• Distribution divided into four equal parts
  
• Q1= 25^th percentile (score at which 25% of the distribution’s value fall below)
  
• Q2= 50^th percentile
  
• Q3= 75^th percentile
  

• Experiment which compares two or more interventions 
• Intervention is compared to control intervention (= no intervention or another type of intervention)
• Participants for each intervention are randomly assigned
• Common assignment to group: one intervention assigned to each individual
• Cluster-randomization: assignment to defined groups of individuals (e. g. class, household)
• Example:

Randomized-Controlled Trial: Treatment success for patient A with drug A in comparison to treatment success for patient B with already existing drug B

Cluster-Randomised-Controlled Trial: Prevalence of obesity in a community with a systematic physical activity program versus a community without any such program

• Difference between lowest and highest value
  
• Formula: R= Maximum- Minimum
  
• Example:

• Measurement scale; interval known with 0 point
• Type of data: metric, quantitative, discrete or continuous
• Example: BMI, cigarettes per day, age, etc.

• Risk of a certain event happening in one group versus the same event happening in another group
• Usually related to risk factor exposure group versus control group
• Ranges:

• Example: RR= 1.3 for lung cancer in smokers compared to non-smokers

• Reproducibility of a study
• Example: