Preview

Random Sampling Method

Good Essays
Open Document
Open Document
378 Words
Grammar
Grammar
Plagiarism
Plagiarism
Writing
Writing
Score
Score
Random Sampling Method
Samples and Sampling

The term "sampling," as used in research, refers to the process of selecting the individuals who will participate (e.g., be observed or questioned) in a research study.
A sample is any part of a population of individuals on whom information is obtained. It may, for a variety of reasons, be different from the sample originally selected.
Samples and Populations

The term "population," as used in research, refers to all the members of a particular group. It is the group of interest to the researcher, the group to whom the researcher would like to generalize the results of a study.
A target population is the actual population to whom the researcher would like to generalize; the accessible population is the population to whom the researcher is entitled to generalize.
A representative sample is a sample that is similar to the population on all characteristics.

Two-stage random sampling A process in which clusters are first randomly selected and then individuals are selected from each cluster.
Stratified random sampling The process of selecting a sample in such a way that identified subgroups in the population are represented in the sample in the same proportion as they exist in the population.
Random sampling Methods designed to select a representative sample by using chance selection so that biases will not systematically alter the sample.
Cluster random sampling The selection of groups of individuals, called clusters, rather than single individuals. All individuals in a cluster are included in the sample; the clusters are preferably selected randomly from the larger population of clusters.

Random Sampling Methods

A simple random sample is a sample selected from a population in such a manner that all members of the population have an equal chance of being selected.
A stratified random sample is a sample selected so that certain characteristics are represented in the sample in the same proportion as they occur in the

You May Also Find These Documents Helpful

  • Good Essays

    Qnt 561 Week2

    • 1289 Words
    • 6 Pages

    For example, if I want to take an example of nation which is combined unit of states. I can choose the random samples of states which can be further divided into smaller units like cities. These cities can be clustered into smaller areas for observation. Researchers can define his pattern of selecting the sample data until data condition of observation is fully satisfied.…

    • 1289 Words
    • 6 Pages
    Good Essays
  • Better Essays

    A population is the total of all the individuals or objects that could be observed or measured. A sample is a subset or portion of a population. Sample should represent the population with fewer but sufficient number of items. One Population can have several…

    • 1640 Words
    • 7 Pages
    Better Essays
  • Satisfactory Essays

    Ap Psychology Quiz

    • 564 Words
    • 3 Pages

    |B) |A sample is a group of subjects selected from a population to be studied. |…

    • 564 Words
    • 3 Pages
    Satisfactory Essays
  • Good Essays

    Amu Quiz 1- Math 302

    • 1504 Words
    • 7 Pages

    What type of sampling is being employed if the population is divided into economic classes and…

    • 1504 Words
    • 7 Pages
    Good Essays
  • Good Essays

    Siop Lesson Plan

    • 856 Words
    • 4 Pages

    CCSS.Math.Content.7.SP.A.2 Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be.…

    • 856 Words
    • 4 Pages
    Good Essays
  • Powerful Essays

    Other Terms Population: entire group of people being studied Sample: the part of the population being studied Inference: conclusion made about the population based on the sample Binary Data: only 2 choices/outcomes Non-Binary: more than 2 outcomes Sampling Techniques Characteristics of a good sample -Each person must have an equal chance to be in the sample -Sample must be vast enough to represent Simple Random: each member has equal chance of being selected Ie, picking members randomly apartments Sequential Random: go through population sequentially and select members Ie, Selecting every 5th person Stratified Sampling: a strata is a group of people that share common charactoristics Constraints the proportion of members in the strata from the population in the sample…

    • 2372 Words
    • 10 Pages
    Powerful Essays
  • Powerful Essays

    Representative Sample p.14: sample selected so that it reflects the characteristics of a population of interest to the researcher.…

    • 4430 Words
    • 18 Pages
    Powerful Essays
  • Good Essays

    The core of biostatistics consists of the definition of a population and sampling, as they are the indicators of the fundamental concepts that are essential to understanding the statistics of the life and health sciences. The idea that a sample is illustrative of a given population, since a sample is derived from a specific, yet larger pool of information seems factually representative. Random sampling aides research in that it applies experimental design to the selection process and is the fairest means of sample collection, providing equal chance to the members of a given population being signified.…

    • 855 Words
    • 4 Pages
    Good Essays
  • Good Essays

    statistics GCU

    • 2646 Words
    • 11 Pages

    Probability sampling, also known as random sampling, requires that every member of the study population have an equal opportunity to be chosen as a study subject. For each member of the population to have an equal opportunity to be chosen, the sampling method must select members randomly. Probability sampling allows every facet of the study population to be represented without researcher bias. Four common sampling designs have been developed for selection of a random sample: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling (Burns & Grove, 2007). Simple random sampling is achieved by random selection of members from the sampling frame. The random selection can be accomplished many different ways, but the most common is using a computer program to randomly select the sample. Another example would be to assign each potential subject a number, and then randomly select numbers from a random numbers table to fulfill the required number of subjects for the sample. Stratified random sampling is used when the researcher knows some of the variables within a population that will affect the representativeness of the sample. Some examples of variables include age, gender, ethnicity, and medical diagnosis. Thus, subjects are selected randomly on the basis of their classification into the selected stratum. The strata ensure that all levels of the variable(s) are represented in the sample. For example, age could be the variable, and after stratification, the sample might include equal numbers of subjects in the established age ranges of 20–39, 40–59, 60–79, and over 80. Researchers use cluster sampling in two different situations: (1) when the time and travel necessary to use simple random sampling would be prohibitive, and (2) when the specific elements of a population are…

    • 2646 Words
    • 11 Pages
    Good Essays
  • Good Essays

    A random sample: is a sample that fairly represents a population because each member has an equal chance of inclusion. Random sampling is the best technique for gathering survey data.…

    • 1431 Words
    • 6 Pages
    Good Essays
  • Satisfactory Essays

    dq 1 module one

    • 585 Words
    • 2 Pages

    Sampling is a sub collection of subjects in a population, for a specific study. There were five techniques discussed in the “visual learner: statistics” four were probability techniques and one was nonprobability.…

    • 585 Words
    • 2 Pages
    Satisfactory Essays
  • Powerful Essays

    A population is the entire group to be studied and a sample is a portion of the population.…

    • 3045 Words
    • 13 Pages
    Powerful Essays
  • Satisfactory Essays

    PSY 211

    • 473 Words
    • 2 Pages

    • representative sample A selected segment o that very closely parallels the larger population o being studied on relevant characteristics. • random selection Process in which o subjects are selected randomly from a larger o group such that every group member has an o equal chance of being included in the study. • correlational study A research strategy o that allows the precise calculation of how o strongly related two factors are to each other. • correlation coeffi cient A numerical indication…

    • 473 Words
    • 2 Pages
    Satisfactory Essays
  • Satisfactory Essays

    Cafs irp

    • 440 Words
    • 2 Pages

    Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations…

    • 440 Words
    • 2 Pages
    Satisfactory Essays
  • Good Essays

    The purpose of sampling is that if a researcher decides to research a group, a group can be very large that the information obtained may not be completely accurate. A researcher can get better information by breaking down the groups into smaller groups and researching them (Monette, 2011). An example of sampling in this case is the large group would be people with PTSD and it can be broken down smaller like researching veterans with PTSD. By breaking the group down for sampling, the data can be obtained more quickly and it is a feasible way of collection. There are types of sampling called probability and nonprobability.…

    • 908 Words
    • 3 Pages
    Good Essays