Podcast
Questions and Answers
What is the primary characteristic of quantitative research?
What is the primary characteristic of quantitative research?
- It uses numbers and statistics. (correct)
- It examines unique case scenarios.
- It focuses on narratives and descriptions.
- It tests hypotheses through qualitative analysis.
Which study design is used to determine cause-and-effect relationships?
Which study design is used to determine cause-and-effect relationships?
- Descriptive Research
- Case Study
- Correlational Study
- Experimental Design (correct)
What is a defining feature of a quasi-experimental design?
What is a defining feature of a quasi-experimental design?
- It focuses on qualitative assessments.
- It includes random assignment of subjects.
- It lacks random grouping of participants. (correct)
- It explores relationships through surveys.
In the context of research design, what is the purpose of specifying the locale of a study?
In the context of research design, what is the purpose of specifying the locale of a study?
Which of the following best describes a descriptive study design?
Which of the following best describes a descriptive study design?
What is the primary purpose of a sample in research?
What is the primary purpose of a sample in research?
Why might a researcher choose to study at a specific locale, such as a school?
Why might a researcher choose to study at a specific locale, such as a school?
Which research approach combines quantitative and qualitative methods?
Which research approach combines quantitative and qualitative methods?
What sampling technique was used to select participants in the study?
What sampling technique was used to select participants in the study?
What is the main purpose of descriptive statistics in this research?
What is the main purpose of descriptive statistics in this research?
Which measure indicates the middle score in a distribution?
Which measure indicates the middle score in a distribution?
What aspect does the 'skewness' measure in data distribution?
What aspect does the 'skewness' measure in data distribution?
In the context of inferential statistics, what does a p-value less than 0.05 indicate?
In the context of inferential statistics, what does a p-value less than 0.05 indicate?
Which statement about the instruments used in data gathering is true?
Which statement about the instruments used in data gathering is true?
What does variance represent in a dataset?
What does variance represent in a dataset?
What ethical consideration must be ensured during the study?
What ethical consideration must be ensured during the study?
Flashcards
Research Design
Research Design
A plan for collecting, analyzing, and interpreting information to answer a research question.
Quantitative Research
Quantitative Research
Research that uses numbers and statistics to find patterns and relationships, often testing hypotheses.
Qualitative Research
Qualitative Research
Research that uses words and observations to understand experiences and perspectives.
Experimental Design
Experimental Design
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Correlational Design
Correlational Design
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Sample Size
Sample Size
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Locale of the Study
Locale of the Study
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Sample
Sample
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Stratified Random Sampling
Stratified Random Sampling
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Inclusion/Exclusion Criteria
Inclusion/Exclusion Criteria
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Frequency Distribution
Frequency Distribution
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Mode
Mode
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Mean
Mean
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Standard Deviation
Standard Deviation
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T-Test for Dependent Samples
T-Test for Dependent Samples
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P-value less than 0.05
P-value less than 0.05
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Study Notes
Research Design
- A research design is a plan for collecting, analyzing, and interpreting data to answer a research question.
- It guides the research study.
- Research Approach: The general way to study a topic.
- Quantitative Research: Uses numbers and statistics to find patterns and relationships, often testing hypotheses.
- Qualitative Research: Uses words and observations to understand experiences and perspectives.
- Study Design: The specific plan for conducting the research.
- Experimental: Tests cause-and-effect by manipulating one factor to see its impact.
- Quasi-Experimental: Similar to experimental, but lacks random assignment.
- Correlational: Investigates connections between two or more variables; does not show cause-and-effect.
- Descriptive: Explores and describes a topic without predictions.
- Case Study: Focuses on a detailed study of one example or situation.
Locale of the Study
- Locale: The location where research takes place.
- Includes: geographic location, demographics (population size, diversity, socioeconomic status), relevant history/culture, facilities, and a justification for choosing that location.
Sample
- Sample: The group of people studied.
- Includes: sample size, sampling technique (e.g., random, stratified), participant details (age, gender, grade level), inclusion/exclusion criteria.
Instruments
- Instruments: Tools used to gather data (e.g., surveys, interviews).
- Includes: type of instrument, source (created or adapted), reliability, and validity.
Data Gathering Procedure
- Step-by-step explanation of how data is collected.
Data Analysis Procedure
- Description of how the collected data will be processed and understood (e.g., statistical tests, themes).
Ethical Considerations
- Explanation of how ethical considerations are addressed (e.g., participant privacy, consent, avoiding harm).
Descriptive Statistics
- Purpose: Summarize and describe data.
- Tools:
- Frequency Distribution: Number of cases in each category.
- Proportion: Frequency divided by total cases.
- Percentage: Proportion expressed as a percentage.
- Measures of Central Tendency: Typical score.
- Mode: Most frequent score.
- Median: Middle score.
- Mean: Average score.
- Variability/Dispersion: How scores differ.
- Range: Difference between highest and lowest values.
- Average Deviation: Average of deviations from the mean.
- Variance: Square of the standard deviation.
- Standard Deviation: Square root of the variance.
Inferential Statistics
-
Purpose: Use sample data to make predictions about a larger population.
-
Parametric Tests: Require normally distributed data.
- Testing Normal Distribution:
- Skewness: Measures symmetry. ±1 suggests non-normality.
- Kurtosis: Measures peakiness. ±1 suggests non-normality.
- T-Tests: Used to compare means.
- T-Test for Dependent Samples: Compares means of two related datasets (e.g., before/after).
- Decision Rule: Reject null hypothesis if p-value < 0.05.
- Testing Normal Distribution:
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Description
This quiz covers the fundamental aspects of research design, including different research approaches like quantitative and qualitative methods. You'll explore various study designs such as experimental, quasi-experimental, correlational, descriptive, and case studies. Test your knowledge and understanding of how research questions are answered through structured designs.
