Quantitative Research: Sampling Techniques

Quantitative Research: Sampling

• Sampling is the process of selecting participants from a larger group (population) for a study.
• Quantitative studies often use representative samples to generalize findings.
• Probability sampling methods ensure each member has an equal chance of selection.
• Non-probability sampling methods don't guarantee equal chance.

Probability Sampling Methods

• Simple Random Sampling: Each member of the population has an equal chance of selection. This is often called the "fishbowl" technique.
• **Stratified Random Sampling:**Dividing the population into subgroups (strata) and taking random samples from each. This ensures representation from different sub-groups.
• Systematic Random Sampling: Select members systematically, at regular intervals. Useful when populations are large. Start by selecting a random starting point, then take every 𝑘th item.
• Cluster or Area Sampling: Select clusters of the population (e.g., geographical clusters). Within clusters, individual participants may then be selected randomly. Used when populations are spread over a large geographical region, making simple sampling challenging.

Non-probability Sampling Methods

• Accidental or Convenience Sampling: Participants are selected based on convenience, without a specific method to ensure representation.
• Quota Sampling: Selecting a predetermined proportion of participants representing population subgroups based on established ratios.
• Snowball Sampling: Participants identify other potential participants, often used for difficult-to-reach populations.

Choosing a Quantitative Research Design

• A decision tree considers research objectives (retrospective vs. predictive vs. explanatory) and time dimensions, whether data is collected once(cross-sectional) or over time(longitudinal), as well as if an intervention is present or not.

Instrumentation for Quantitative Research

• Instrumentation involves collecting data using tools or devices (instruments).
• Key questions to address during instrument development include how/when/where data will be collected and analyzed.
• Instruments can include questionnaires, interviews, observations, or standardized tests.

Research Instruments Common Types

• Surveys/Questionnaires: A set of written or digital questions that collect data on opinions, behaviors, or other characteristics. Can have open-ended or close-ended questions.
• Scales: Structured instruments with specific answer options (e.g., Likert scales) used to classify and measure data. Scales can measure attitudes, opinions, or perceptions.

Data Analysis in Quantitative Research

• Descriptive Statistics: Procedures that describe data in a summarized form, like calculating frequencies, percentages, or measures of central tendency (mean, median, mode). Pie charts and bar graphs are useful for visualizing data.
• Inferential Statistics: Used to make inferences or generalizations about a larger population based on data collected from a sample. This involves hypothesis testing to determine the statistical significance of findings. Error rates (Type I & Type II) are also important to consider. Various statistical tests are used depending on the design and data type.

Measures of Central Tendency

• Mean: The average of a data set.
• Median: The middle value in a sorted data set.
• Mode: The most frequent value in a data set.

Measures of Variability

• Range: The difference between the highest and lowest values in a data set.
• Standard Deviation: A measure of how spread out data is from the mean.
• Variance: The square of the standard deviation.

Data representation in a Research Study

• Pie charts and bar graphs effectively visualize data distributions. Frequency counts quantify observations.

Research Ethics

• Informed consent: Participants know the purpose, procedures, risks, and benefits of the study before agreeing to participate.
• Confidentiality: Safeguarding participants' identities and preserving privacy.
• Integrity: Maintaining honesty in data collection, analysis, and reporting.

Quantitative Data Analysis

• Includes analyzing numerical data, conversions if needed, and hypothesis testing.

This quiz explores various sampling methods used in quantitative research. It covers probability sampling techniques like simple random, stratified, systematic, and cluster sampling. Test your knowledge on how these methods ensure accurate representation in studies.