Quantitative & Qualitative Methods Flashcards
7 cards from real CRA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Quantitative & Qualitative Methods flashcards as text
In a chi-square test of independence, the null hypothesis states that:
Answer: The two categorical variables are independent of each other
The chi-square test of independence tests whether two categorical variables are associated, with the null assuming no relationship between them.
A researcher uses purposive sampling in a qualitative study. The main goal is to:
Answer: Select information-rich cases that best address the research question
Purposive sampling deliberately selects participants based on specific characteristics relevant to the research question, prioritizing depth over representativeness.
When a researcher uses triangulation in a mixed-methods study, the primary purpose is to:
Answer: Cross-validate findings from different data sources or methods
Triangulation uses multiple methods, data sources, or researchers to cross-validate findings and enhance the credibility of conclusions.
A Type II error in hypothesis testing occurs when the researcher:
Answer: Fails to reject a false null hypothesis
A Type II error (beta error) occurs when a researcher fails to detect a real effect because the null hypothesis is not rejected even though it is false.
In grounded theory, theoretical sampling means:
Answer: Selecting cases based on emerging theory to further develop and saturate categories
Theoretical sampling in grounded theory involves collecting data guided by the emerging theory, continuing until theoretical saturation is reached.
Cronbach's alpha is a measure of:
Answer: Internal consistency reliability
Cronbach's alpha assesses internal consistency by measuring how closely related a set of items are as a group, indicating whether they measure the same construct.
Which characteristic distinguishes a probability sample from a non-probability sample?
Answer: Every member of the population has a known, non-zero chance of selection
In probability sampling, each population element has a known, non-zero probability of being selected, enabling generalization and statistical inference.