Unit 10: Data Analysis Practice Flashcards

A set of vocabulary-style flashcards covering quantitative and qualitative data analysis strategies, levels of measurement, and data quality/trustworthiness as defined in the Unit 10 study notes.

Descriptive statistics

Statistics used to summarize the data collected, with common examples being frequency, percentage, mean, median, mode, range, and standard deviation.

Inferential statistics

The use of sample data to test hypotheses or draw conclusions about a larger population.

Mean

The average of a set of values, calculated by adding all values and dividing by the number of values.

Median

The middle value after numbers are placed in order; with an even number of values, it is the average of the two middle values.

Mode

The value or category that occurs most often in a data set.

Range

The highest value minus the lowest value, used to show the spread of scores.

Nominal Measurement

Categories with no meaningful order, such as blood type, diagnosis, or hospital unit.

Ordinal Measurement

Ordered categories where the distance between categories is not known to be equal, such as rankings or satisfaction ratings.

Interval Measurement

Ordered numerical values with equal intervals but no true zero, where $0$ does not mean none of the characteristic.

Ratio Measurement

Ordered numerical values with equal intervals and a true zero, where $0$ represents none of the measured amount.

Reliability

The ability of a scale or measurement tool to produce consistent results with little measurement error.

Validity

The degree to which a scale or tool measures what it is intended to measure.

Generalizability

The extent to which findings can be applied beyond the study sample to other people, settings, or situations.

Clinical significance

A determination of whether a finding is large or important enough to matter in real practice.

Statistical significance

Whether a result is unlikely to be due to chance according to the chosen statistical cutoff.

Codes

Labels used for important sections of raw qualitative data, such as interviews or field notes.

Categories

Groups of similar codes used during the qualitative data analysis process.

Theme

A major pattern or idea developed across qualitative data that should be supported by participants’ quotations or raw data.

Credibility

Confidence that qualitative findings accurately represent participants’ experiences, often established through member checking or prolonged engagement.

Dependability

The consistency and logical documentation of the research process, ensuring another researcher could understand how decisions were made.

Confirmability

Evidence that findings come from the data rather than the researcher’s preferences, often involving audit trails and reflexive notes.

Transferability

The provision of enough detail for readers to judge whether findings may apply in another setting or group through rich description of participants and context.