Philosophy of Science Fundamentals

Ontology: the study of existence, exploring what entities exist, their properties, and relationships.
Axiology: the branch of philosophy dealing with values, including ethics (moral values) and aesthetics (beauty and art).
Metaphysics: the branch of philosophy concerned with the fundamental nature of reality, investigating existence, time, space, and mind-matter relationships.
Epistemology: not explicitly defined in the text, but refers to the study of knowledge and how it is acquired.

Authority: knowledge obtained from experts, scholars, or reputable texts, relying on expertise and credibility.
Deduction: deriving specific conclusions from general principles or premises using logical inference.
Induction: drawing general conclusions based on specific observations or patterns, moving from specific instances to formulating general principles.
Intuition: knowledge gained through instinctive or immediate understanding without conscious reasoning or inference.

Experimental research: manipulating variables, using random assignment and control groups to assess causal relationships.
Time series and single-subject designs: collecting repeated measurements over time to assess changes or trends, and focusing on individual cases with baseline and intervention phases.

Independent variable: the variable manipulated or controlled by the researcher, hypothesized to affect the dependent variable.
Dependent variable: the variable measured or observed in response to the independent variable, hypothesized to be influenced by the independent variable.
Antecedent variable: a variable that precedes or comes before the independent variable in time, potentially a confounding variable.
Treatment variable: a specific condition or intervention applied to participants in an experimental study.
Outcome variable: the variable representing the result or consequence of an event, treatment, or phenomenon.
Predictor variable: a variable used to predict or estimate the value of another variable.
Confounding variable: an extraneous variable associated with both the independent and dependent variables, potentially influencing the relationship between them.

Continuous variables: can take any value within a certain range, measured on a continuum (e.g. height, weight).
Discrete variables: can only take specific values, often representing categories or counts (e.g. number of children, type of car).
Ratio scale: a measurement scale with a true zero point and equal intervals between values, allowing for comparison or ratios (e.g. age, income).
Interval scale: a measurement scale with equal intervals between values but no true zero point, not allowing for ratio comparisons (e.g. temperature on Celsius or Fahrenheit scales).
Ordinal variables: representing distinct categories or groups with an inherent order.

Probability samples: each member of the population has an equal chance of being selected, ensuring representativeness.
Nonprobability samples: do not use random selection, may have limited generalizability.
Simple random sampling: each member of the population has an equal chance of being selected, using a random number generator.
Systematic sampling: selecting every 5th individual from the population, with the first individual randomly selected.
Stratified random sampling: dividing the population into homogeneous subgroups, selecting a random sample from each stratum in proportion to its size.
Cluster sampling: dividing the population into groups, randomly selecting a few clusters, and including all individuals within the selected clusters.
Consecutive sampling: including all individuals who meet the inclusion criteria and are encountered within a specific time frame or at a particular location.
Convenience sampling: selecting a sample based on convenience or availability, often with limited generalizability.

Accuracy: the closeness of a measurement value or result to the true or target value, assessing the absence of systematic errors.
Precision: the consistency and reproducibility of measurements, measuring the degree of agreement between repeated measures.
Reliability: the consistency of stability of a measuring instrument or research findings, indicating the extent to which the same results can be obtained under similar conditions.
Validity: the extent to which a measuring instrument or research study accurately measures what it intends to measure, assessing the truthfulness or accuracy of the inferences or conclusions drawn.

Efficacy and effectiveness of care: understanding the effectiveness of healthcare interventions and treatments is crucial for providing evidence-based care and improving patient outcomes.
Contributions to theory: advancing theoretical frameworks in allied health research helps to enhance understanding, explain phenomena, and guide future research and practice.