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Sampling

By Janie Solinski-Ruddy

+The Validity of Your Inferences is Dependent upon Your Sample.

• A ‘sample’ is a small representation of a larger population.

• Generalizations cannot be made about the larger population if you do not have an accurate sample.

• Example: You want to find out how far the average male can run, but your ‘sample’ was taken from a Nursing Home. Does this sample, no matter how large, represent the population in general, if the mean age is 32 years old?

• Discuss another example of a sample that would not represent the total population.

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+Representative Samples Have The Same Characteristics as The General Population.

If the mean age of the men being studied in the previous example is 32 years old with the range being from 10 years to 70 years, then your sample should also have this characteristic.

If asthma occurs 10% of the time in the general population, then asthma should also occur 10% of the time in your representative sample.

Discuss with your group two other characteristics that might be accounted for when studying the distance an average male can run.

+The Group Selected in a Random Sample is Chosen by Chance This reduces the chance of bias.

Larger sample sizes are needed to be able to make accurate inferences.

Keeping in mind the difference between random sampling and representative sampling, develop a sampling plan to choose our crickets for our study

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Gallery Walk

Use the large piece of bulletin paper to display your sampling plan.

Once all groups are finished, use the post-it notes to give each group feedback.

You will have three minutes at each plan to provide your feedback.