Quantitative Methods and Research

These flashcards cover key concepts from the Quantitative Methods lecture notes, including research characteristics, sampling techniques, correlation and causation, measurement scales, and reliability and validity in research.

What are the primary characteristics of quantitative research?

Focus on numbers, use of close-ended questions, testing objective theories.

What does the term 'positivism' refer to in research?

The belief that theories must be tested and refined for prediction and understanding.

What is a key feature of a positive correlation?

As one variable increases, the other variable also increases.

How can causation be established in research?

Through experimental studies that control for other variables rather than observational studies.

What is sampling bias?

A flaw in data collection where certain parts of the population are favored.

What is a good sampling method to ensure representativeness?

Random sampling, where each individual has an equal chance of being selected.

What is the difference between a convenience sample and a voluntary response sample?

A convenience sample comprises people who are easy to reach, while a voluntary response sample consists of self-selected participants.

What is non-response bias?

A bias that occurs when the responses received are not representative of the total population.

What is an example of quantitative data?

Hours studied per week or number of siblings.

What does reliability refer to in quantitative research?

The consistency or repeatability of a measure over time.

What is the difference between validity and reliability?

Validity measures whether the instrument accurately measures what it intends to, while reliability measures the consistency of the results.

What are the four scales of measurement in research?

Nominal, ordinal, interval, and ratio scales.

Give an example of an ordinal scale.

Race placements such as 1st, 2nd, and 3rd.

What does it mean if a measure is reliable but not valid?

It consistently yields the same results but does not measure what it is supposed to measure.