Practical Research 2: Quantitative Design & Sampling
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Questions and Answers

What is the main characteristic of cluster sampling?

  • The population is divided into clusters, and random samples are taken from each cluster. (correct)
  • Samples are taken randomly from the entire population.
  • Individuals are selected based on their availability.
  • Population is stratified into groups without random selection.

    • Stratified sampling ensures that every subgroup of the population is represented in the sample.

    True (A)

    What is non-probability sampling?

    Sampling methods where individuals are selected based on non-random criteria.

    In _____ sampling, the nearest available individuals are chosen until the desired sample size is reached.

    <p>convenience</p> Signup and view all the answers

    Match the following sampling techniques with their descriptions:

    <p>Stratified Sampling = Ensures representation from all subgroups Cluster Sampling = Divides population into clusters for sampling Convenience Sampling = Selects based on availability Purposive Sampling = Selects based on specific criteria or purpose</p> Signup and view all the answers

    Which of the following is a characteristic of purposive sampling?

    <p>Individuals are chosen for their specific characteristics or qualities. (C)</p> Signup and view all the answers

    Multistage sampling is a method that requires only one round of random sampling.

    <p>False (B)</p> Signup and view all the answers

    List one example of a study that may use purposive sampling.

    <p>Antimicrobial Activity of Mango Peel</p> Signup and view all the answers

    Which of the following experimental designs requires random assignment of subjects to groups?

    <p>True experimental studies (C)</p> Signup and view all the answers

    Pre-experimental studies are the most reliable type of experimental design.

    <p>False (B)</p> Signup and view all the answers

    What design involves at least two groups, where one group receives treatment and both are post-tested?

    <p>Posttest-only control group design</p> Signup and view all the answers

    In a one group pretest-posttest design, the notation for the control group is represented as _ _ _ _ _ _ O2.

    <p>O1</p> Signup and view all the answers

    Match the following experimental designs with their key characteristics:

    <p>True Experimental = Requires control group and random assignment Quasi-experimental = Lacks randomization but has treatment Solomon Four Group = Investigates interactions of multiple variables One Shot Case Study = Measures change without conclusive results</p> Signup and view all the answers

    Which design is characterized by involving four groups with different pretesting statuses?

    <p>Solomon Four Group Design (C)</p> Signup and view all the answers

    In a static group comparison, both groups receive a post-test after exposure to treatment.

    <p>False (B)</p> Signup and view all the answers

    Describe the major limitation of a one shot case study.

    <p>It cannot provide conclusive results.</p> Signup and view all the answers

    Which research design involves comparing pretest and posttest data with a controlled setup?

    <p>Pretest-Posttest with Control Group (D)</p> Signup and view all the answers

    In systematic sampling, the selection of sample elements is entirely random without a specific order.

    <p>False (B)</p> Signup and view all the answers

    What is the primary goal of using stratified random sampling?

    <p>To ensure that specific subgroups are appropriately represented in the sample.</p> Signup and view all the answers

    A _________ sample is selected by judgment and does not give all units an equal chance of being chosen.

    <p>Non-Probability</p> Signup and view all the answers

    Match the sampling methods with their descriptions:

    <p>Simple Random Sampling = Each unit has an equal chance of being included in the sample Stratified Random Sampling = Population divided into groups, with random samples from each Systematic Sampling = Sample elements are included based on a systematic calculation Cluster Sampling = Population is divided into clusters, and entire clusters are randomly selected</p> Signup and view all the answers

    What advantage does probability sampling have over non-probability sampling?

    <p>Fewer errors in data (D)</p> Signup and view all the answers

    Cluster sampling selects individuals from a population in non-structured groups.

    <p>True (A)</p> Signup and view all the answers

    Describe one advantage of using a sample rather than studying the entire population.

    <p>It saves time and resources while still providing useful insights.</p> Signup and view all the answers

    Flashcards

    Population

    The entire group of individuals or objects that a researcher is interested in studying.

    Random Sampling

    A sampling technique where every member of a population has an equal chance of being selected.

    Stratified Sampling

    Dividing the population into subgroups (strata) and taking a random sample from each.

    Cluster Sampling

    Dividing the population into clusters, randomly selecting some clusters, and then collecting data from all members of the selected clusters.

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    Multistage Sampling

    Using more than one round of random sampling to collect data.

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    Convenience Sampling

    Choosing participants who are readily available.

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    Non-Probability Sampling

    Sampling methods where not every member of the population has an equal chance of being selected.

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    Purposive Sampling

    A sampling technique where participants are chosen based on specific characteristics or traits.

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    Research Design: Pretest-Posttest with Control Group

    A research design where a group is tested before and after a treatment, while a separate control group is not treated. Researchers compare the outcomes of both.

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    Research Design: Randomized Complete Block Design

    A design used in experiments where the researcher divides the participants or samples into groups called blocks. Then, participants within each block are randomly assigned to different treatments.

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    Sample

    A smaller group selected from a population to represent the entire population.

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    Probability Sampling

    A sampling technique where every member of the population has a known, non-zero probability of being selected.

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    Simple Random Sampling

    A probability sampling technique where every member of the population has an equal chance to be chosen.

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    Systematic Sampling

    A sampling approach where every nth item or member of the population is selected from a list or sequence to form the sample.

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    Stratified Random Sampling

    A technique for probability sampling that divides the population into subgroups or strata. Then, participants are randomly chosen within from each of these subgroups

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    True Experiments

    Research designs that involve a control group, random assignment of participants, and manipulation of an independent variable to measure its effect on a dependent variable.

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    Quasi-Experiments

    Research designs used when true experimentation isn't possible due to ethical or practical reasons. They lack random assignment.

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    Pre-experimental Studies

    Research designs conducted before a main experiment to assess the influence of variables potentially affecting study groups.

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    Posttest-Only Control Group Design

    An experimental design with two groups, one exposed to a treatment (experimental), the other not (control). Both are measured after the treatment.

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    Pretest-Posttest Control Group Design

    An experimental design that compares a treatment group and a control group using both pre and post measurements to see if there are changes after the treatment.

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    Solomon Four-Group Design

    Experimental design with four groups, two with pretests and two without pretests. This allows for comparison and assessment for the effects of the pretest itself.

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    Static Group Comparison

    An experimental design comparing two existing groups. One group receives a treatment, both are measured after the treatment.

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    One-Group Pretest-Posttest Design

    A single group is measured before and after a treatment, and conclusions about change can't be definitively linked to the treatment.

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    Study Notes

    Course: Practical Research 2

    • Week: 2
    • Quarter: Second
    • Type: Quantitative Research Design and Sampling

    Objectives

    • Choose appropriate quantitative research design (CS_RS12-lla-c-1)
    • Describe sampling procedure and the sample (CS_RS12-lla-c-2)
    • Discuss research design and sampling

    Importance of Chapters 1 & 2

    • Understanding the importance of properly writing Chapters 1 and 2 of a research paper.
    • Establishing the connection between the two chapters.
    • Identifying the meaning behind the photos/images.

    Purpose of Methodology

    • Describe the research design (or defend it)
    • Provide enough details for another researcher to repeat the experiment

    Research Process

    • Define Research Problem
    • Review the Literature
    • Formulate Hypothesis
    • Design Research
    • Collect Data
    • Analyze and Present Data
    • Interpret and Report

    Research Design

    • A strategy to integrate different study components logically.
    • Acts as a blueprint for collecting, measuring, and analyzing data.

    Terms to Know

    • Replication
    • Local Control
    • Randomization
    • Control of Extraneous Variables

    Types of Quantitative Research Designs

    • Descriptive: Used as a precursor to other research designs, yielding data for recommendations and analysis
    • Survey, Observational, Correlational, Comparative, Developmental, Evaluation, Trend Analysis: Types of descriptive research designs
    • Survey Research: Aims to build norms and standards based on survey data; local control and control of variables depend on the survey questions.
    • Correlational Studies: Estimate the relationship between variables in a population.
    • Comparative Studies: Compare the occurrences/nature of multiple variables on samples/subjects across the same period.
    • Causal-Comparative: Measures the impact of a change on existing norms/assumptions. Attempts to establish a causal link and eliminates alternative possibilities. Also called quasi-experimental
    • Pre-experimental: Commonly avoided due to lacking randomization but beneficial to see group influence
    • One Shot Case Study: The least reliable experimental approach; indicated with G: X—O
    • One Group Pretest-Posttest Design: Measures change but yields inconclusive results; indicated with G: 01—X—02
    • Static Group Comparison: Two or more groups; one exposed to treatment and both post-tested; indicated with G1: X—02; G2: 02
    • True Experimental Studies: Require a control group, random subject assignment, and the dependent variable reflects the independent variable's effect
    • Posttest-Only Control Group Design: At least two groups; one group receives treatment, both post-tested; indicated with R1 : X—O2; R2: O2
    • Pretest-Posttest with Control Group: At least two groups, both pretested; one group receives treatment, both post-tested; indicated as R1: 01—X—02; R2: 01—02
    • Solomon Four Group Design: Four groups—two pretested, two not; groups 1 and 3 receive treatment, while 2 and 4 don't; all four post-tested; indicated with R1: 01—X—02; R2: 01—02; R3: X—02; R4:02.
    • Factorial Design: Allows examination of multiple independent variables' interaction and effect on dependent variables.
    • Completely Randomized Design: Random assignment in groups and treatments.
    • Randomized Complete Block Design: Commonly used for agricultural experiments, grouping similar experimental units into blocks.

    How to write Research Design for Chapter 3:

    • Briefly state the overall design (qualitative or quantitative).
    • Specify the observed design in the study.
    • Define the design (1-2 sentences) and cite.
    • Explain how the design will be used in the research.

    Scenarios for Research Design

    • Scenario 2: Researchers measure initial pear weight/colour, then test post-testing 26 days later.
    • Scenario 3: Field fertility gradient depicted with varying colors (treatment blocks).

    Sampling Design

    • Sampling: Choosing a representative population portion.
    • Population, Target Population, Sample, Subject, are key sampling terminologies.
    • Probability Sampling (Simple Random, Systematic, Stratified Random, Cluster, Multistage): Characterized by chance mechanism, equal selection chance.
      • Simple Random: Each unit has a chance of inclusion.
      • Systematic: Uses a formula to select certain units from a designated list.
      • Stratified Random: Divides the population into strata/groups to select random simple samples in each group.
      • Cluster Sampling: Divides groups into clusters, randomly selecting clusters to determine a simple random sample
      • Multistage Sampling Using multiple rounds of different sampling techniques
    • Non-Probability Sampling (Convenience, Purposive, Quota, Accidental, Snowball): Characterised by judgement selection, unequal selection chance.
      • Convenience Sampling: Chooses the easiest units/objects available until the desired size is reached
      • Accidental Sampling: Includes available participants without explicit criteria.
      • Quota Sampling: Aims to ensure a proportional segment inclusion in the sample.
      • Purposive Sampling: Focuses on representing the population using evidence; select what the researcher wants
      • Snowball Sampling: Uses network of respondents to refer other respondents

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    Research Design and Sampling Techniques PDF

    Description

    This quiz focuses on understanding quantitative research design and sampling methods as covered in Practical Research 2, Week 2. It aims to help students choose appropriate research designs and describe sampling procedures. Mastery of these concepts is essential for writing effective Chapters 1 and 2 of a research paper.

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