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Learning Goal: I’m working on a statistics discussion question and need the explanation and answer to help me learn.

Suppose you are designing and conducting a poll to see which of the Congressional candidates are popular in your area. Use the terminology and concepts that we are learning in Lesson 1 – population, sample, sampling methods, representative sample, and presentation of data….

  • the population that you are trying to predict,
  • where and how are you selecting your sample,
  • what sampling method would you use,
  • how would you assure that you are selecting a representative sample, and
  • show an example of how you would present your data
  • this assignment is a answer to the discussion as well as a response to a peer.
What Is a Representative Sample?

A representative sample is a subset of a population that seeks to accurately reflect the characteristics of the larger group. For example, a classroom of 30 students with 15 males and 15 females could generate a representative sample that might include six students: three males and three females. Samples are useful in statistical analysis when population sizes are large because they contain smaller, manageable versions of the larger group.


Types of Sampling Methods

Choosing a sampling method can depend on a variety of factors. Representative samples are usually an ideal choice for sampling analysis because they are expected to yield insights and observations that closely align with the entire population group.

When a sample is not representative, it can be known as a random sample. While random sampling is a simplified sampling approach, it comes with a higher risk of sampling error which can potentially lead to incorrect results or strategies that can be costly. Random sampling can choose its components completely at random, such as choosing names randomly from a list. Using the classroom example again, a random sample could include six male students.

Systematic sampling is another type of sampling method that seeks to systemize its components. This type of sampling may include choosing every fifth person from a population list to gather a sample. While this method takes a systematic approach, it is still likely to result in a random sample.

Stratified Random Sampling

Stratified random sampling can be an important part of the process in creating a representative sample. Stratified random sampling examines the characteristics of a population group and breaks down the population into what is known as strata. Dividing out the population by strata helps an analyst to easily choose the appropriate number of individuals from each stratum based on proportions of the population. While this method is more time consuming—and often more costly as it requires more upfront information—the information yielded is typically of higher quality.


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