Percentage change
Final - Initial / Initial x 100
Qualitative variable
Categorical variable that describe attributes or categories rather then using numeric values ( eye colour, place of birth)
Quantitative variable
A variable that measures a numerical quantity or amount, with real numbers
Experimental unit
The individual or subject on where a variable is measured (patient in medical research, plant in botany research)
Independent variable
The predictor or cause of a study. It is what you are changing in the experiment to see if it has an effect or not.
Dependent variable
What changes due to the IV. The outcome or the effect
Confouding variable
A variable not associated with the experiment, potentially distorting the realtionship between IV and DV
Propensity score
The probability of reciving treatment given baseline characteristics, used to balance groups in observational study.
Nominal variable
Qualatiative data that assigns categories with no natrual order (eye colour, placce of birth, religion)
Binary variable
Qualatiative data with only two categories. Is a form of nominal variable (yes/no, dead/alive)
Ordinal
Qualatiative variable that has a logical order to them, but the space inbetween is not measurable (cancer level, education level)
Discrete variable
Whole numbers only (numbers of people)
Continues variable
Quantitative variable that uses any value within a range. Usally is measured and in decimal (Response time, BMI)
Interval variable
Quantitive that has equal numeric spacing however 0 is arbitrary and math cant really be used (temperature as 4c is not twice as hot as 2c)
Ratio variable
Quantitative data with equal spacing and has a true zero point where math an be used (Height, income)
Bias
Systematic error that cuases reulsts ot deviate from the truth
Random error, systemic, and systematic error
Random error = unpredictable fluctuations due to chance.
Systematic error = consistent, reproducible error due to deliberate study design flaws and actions.
Systemic error = integrated within the research design
Internal validity
The extent to which a study is designed, conducted, and analyzed correctly determines the trustworthiness of its results and is specfic to its research question
External validity
The extent to which study findings can be generalized to other settings, populations, or times
Selection bias
Systematic error from differences between study participants and the population of interest (e.g., non-response bias, survivorship bias, loss to follow-up)
Information bias
Systematic error in how data is collected, recorded, or recalled (e.g., observer bias, interviewer bias, recall bias, social desirability bias)
Observational study
Used to observe a phenomenon or create an initial hypothesis. Researchers assess variables without controlling them. Used to determine association and not causation.
Prevalance
The proportion of people with a condition at a specific time (includes both new and existing cases). How prevalent the disease is
Incidence
The rate or proportion of new cases of a condition during a specific period. How many new cases are there.
