Module 1 - Introduction & Overview Flashcards
Case-Control Studies
- Compares 2 groups of samples with similar characteristics (cases & controls)
- In both groups 1/2 of sample is exposed 1/2 is not
- Researchers compare the differences between each group to determine why the cases got the disease
- Observational Study
Categorical Variables
- When values are based on distinct categories of qualities
- Examples: race, gender, religion, etc.
What are the 2 broader classifications of variables?
- Types of Variables
- Types of Scales
Statistics
Data or a number, the process of analyzing the data
A Statistic
A numerical summary of the sample of data
Nominal Scale
- Data is grouped into categories
- Examples: Yes/No; normal, overweight, obese
- Categorical Variables
Population
Total set of subjects of interest in a study
Parameter
A numerical summary of the population based on inferential statistics
Quantitative Variables
- The measurement scale has numeric values
- Examples: annual income, age, years of education completed, etc.
Inferential Statistics
Predicting information about a population based on data from a sample
n=
The total number of subjects in a sample
Variables
Characteristics that vary among subjects in a sample or population
What are the 2 major categories for study designs?
- Observational
- Experimental
Continuous Scale
- Part of Ratio Scale
- Has values on a continuum
- Example: Age
Observational Studies
- Observe the variables without intervention
- Example: Study to see if excessive body fat in children is due to a specific gene
Ordinal Scale
- Observations are grouped into categories, they are often group
- The difference between each category is not specifically defined
- Example: Ranking subject responses in increasing order, the differences between the adjacent subjects aren’t equal
- Categorical Variables
Simple Random Sample
Subjects from a population where each person has an equal chance of being selected
Biostatistics
The application of statistics to medicine/health
Experimental Studies
-Observe variables with intervention and a control group without intervention to compare the results
Ratio Scale
- Scale using numbers, the differences between numbers have meaning on a numerical scale
- AKA Numerical Scale
- Quantitative Variables
Randomization
The process of finding a sample that best represents a population
Interval Scale
- Questions with numeric answers are summed, which creates a scale
- Example: Satisfaction survey, 0 = not satisfied (rather than no value)
- Quantitative variables
Discrete Scale
- Part of Ratio Scale
- Values equal to integers
- Example: Number of injuries
What are Steven’s 4 Scales of Measurement
- Ratio Scale
- Interval Scale
- Nominal Scale
- Ordinal Scale
- *Think RINO**
Subjects
The entity data is collected from, usually people, but can be families, schools, cities, or companies
Cross-Sectional Studies
- Researchers measure the outcome and exposures in the subjects at the same time
- This is commonly used to determine the prevalence of a disease
- Observational Study
Sample
A subset of population that data is collected on
