Differentiate between randomized and nonrandomized approaches to sampling populations.

  • Differentiate between randomized and nonrandomized approaches to sampling populations. Discuss the importance of the role of sampling when conducting research.
  • Snowball sampling is a form of sampling where participants recommend people they know as research participants. Explain one pro and one con to this approach.
  • Discuss the usefulness of pretesting, pilot testing, or field-testing a survey or interview questionnaire.
  • In some large-scale research projects the researcher is not always the one collecting data but is more heavily involved in the analysis and interpretation of the data. Would this create a challenge in a quantitative study where a survey was used for data collection? Would this scenario create a challenge in a qualitative study where a one-to one interview or focus group data collection method was used? Explain why or why not for both scenarios.
  • As you experienced in the Week 3 assignment, qualitative methods research can encompass some interesting forms of research approach to help us understand the human experience in society, such as ethnography. In the resources this week we asked you to review three other forms of approach that help us understand in unique ways: visual, documentary, and oral history.
  • After reviewing the resources provided, describe each form of approach. Explain their unique differences and similarities.
  • What is gained by conveying human experience via visual or audio as opposed to a written interpretation?
  • Which form of approach did you find the most compelling in sharing the experience of humans in society? Explain why.
  • Do you think that these forms of visual and audio data evidence could be more powerful for influencing social change and public policy than written or statistical data? Explain your response.
  • Differentiate between randomized and nonrandomized approaches to sampling populations. Discuss the importance of the role of sampling when conducting research.


    Sampling is a technique used in research to collect data from a population. The goal of sampling is to make sure that you get an accurate representation of the whole group being studied by taking just enough people from it so that the sample reflects the population as closely as possible. The word “sampling” comes from the Latin word “sama”, meaning equal or even, but not necessarily completely representative. Nonrandomized and randomized samples are two different ways of choosing a subset of people for inclusion in an experiment or survey; they differ in how they’re chosen—and thus how much bias there might be—but both have their strengths and weaknesses when it comes to representing populations accurately

    What is sampling?

    Sampling is a method of selecting a sample from a population. It’s used to reduce the cost and time of research, increase the representativeness of the sample, or get data quickly.

    Sampling has two main purposes: 1) to reduce costs by using fewer cases than one would need if one were conducting an experiment with complete information on every participant in the study; and 2) To increase representativeness by concentrating on characteristics common across all members of defined groups (e.g., all women).

    The importance of sampling in research.

    Sampling is important because it can be used to make generalizations about a population, which helps researchers make inferences. Sampling also allows researchers to make predictions about the population and test these predictions in subsequent research.

    Types of nonrandomized sampling.

    Nonrandomized sampling can be used as a way to collect data on a population. In this type of nonrandomized sampling, the researcher selects a group that is representative of the entire population. For example, if you’re conducting research on transgender people and want to know their experiences in your community, then it would be better to select an entirely new group than simply ask them questions about themselves while they are out shopping or at work (i.e., “What do transgender people have trouble with?”).

    Nonrandomized surveys often provide less information than randomized surveys because they rely on individuals’ self-reporting and may not include certain groups within their sample (e.g., women). However, nonrandomized surveys are more practical for smaller studies since they don’t require large numbers of participants who could otherwise take up valuable time from researchers’ limited budgets or resources; furthermore, there is no cost associated with performing these types of studies!

    Types of randomized sampling.

    Randomization is the process of assigning individuals to treatment or control groups using random numbers. It helps ensure that each treatment and control group has an equal chance of being chosen, regardless of their actual characteristics. Randomization can be done in several ways, including:

    • Using a random number generator (RNG) to generate a list of possible values for each variable in your study. This method is often used when you have a large number of variables and don’t know how many will be included in your final analysis plan before starting the study; it also allows you to include as many different types of data as possible. For example, if there are 50 different questions asked on surveys about job satisfaction by employees at one company’s annual survey, then those 50 questions could potentially be used as inputs into a model involving employee satisfaction with their jobs as well as other factors such as wages paid by employers or hours worked per week among workers who were surveyed during this period

    Nonrandomized and randomized samples are different techniques for selecting a representative group.

    • Nonrandomized and randomized samples are different techniques for selecting a representative group.
    • Nonrandomized samples are not selected with a random process, but rather by an investigator who decides which individuals to include in their study. This can result in biases because the researcher has preconceived notions about what groups should be included or excluded from the study.
    • Randomized sampling is more accurate than nonrandomized sampling because it uses a sample that has been randomly divided into subgroups based on certain characteristics such as gender, race/ethnicity, age range (elderly), etc., so there are no differences between any two groups except those due to chance alone–in other words: each person’s chance of being included in either group was equal (or 1).


    Nonrandomized and randomized samples are different techniques for selecting a representative group. The first approach is to choose a random sample of the population, while the second involves selecting potential members of the group at specific points in time. In choosing which approach to use, you should consider whether your research will apply only to people from one particular region or country, or if it’s more generalizable across countries (for example).

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