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Experiments, Surveys, and Observational Studies

Experiments, Surveys, and Observational Studies. Notes. Sometimes we want to know information about groups of people. A population is a large group of individuals you want information about. An individual is defined to include people, animals, or objects that are described by data.

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Experiments, Surveys, and Observational Studies

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  1. Experiments, Surveys, and Observational Studies Notes

  2. Sometimes we want to know information about groups of people. • A population is a large group of individuals you want information about. • An individual is defined to include people, animals, or objects that are described by data. • Realistically, though, would we able to survey everyone in the United States to find out something? • For example, could we ask every American what their favorite food is or who they plan to vote for in an election?

  3. No, we wouldn’t….so how do we get information about such large groups? • A CENSUS • a survey of an entire population • very expensive • time-consuming • A SAMPLE • a group chosen to represent an entire population • less expensive • can be designed to take much less time than a census Example: US Census every 10 years Example: A phone poll asking who you will vote for in an upcoming election

  4. Example: A quality control inspector needs to estimate the number of defective laptops in a group of 250 laptops. He tests 25 randomly chosen laptops. • What is the population? • The population is the group of 250 computers. • What is the sample? • The sample is the group of 25 computers he inspects. Population = entire group Sample = chosen group

  5. More About Samples • Convenience Sample: chooses individuals who are easiest to reach • Example: asking people leaving a grocery store who they are going to vote for in an election • Voluntary Response Sample: individuals respond to a general request • Example: people respond to a survey they received in the mail

  6. These samples choose a sample that is almost certain not to represent the true opinions of an entire population. In other words, they are biased.

  7. Biased – favors certain outcomes • A population might be UNDERREPRESENTED. • one or more parts of a population are left out when choosing the sample • A population might be OVERREPRESENTED. • an emphasis is placed on one or more of the parts of a population

  8. Think about each situation below. Could the sampling method result in a biased sample? Why? Move to the next slide to check your answers. • A survey is conducted by calling 100 people randomly chosen from the phone book and asking them what their favorite kind of toothpaste is. • A restaurant owner wants to know how often families in his area go out for dinner. He surveys 30 families who eat at his restaurant on Tuesday night. Scenario #1 Scenario #2

  9. How well did you do? Compare your thoughts with the answers below. • The random people chosen from the phone book are not necessarily representative of the entire city’s population. • People who aren’t listed in the phone book are excluded. • The sample is a convenience sample, which probably isn’t representative of the entire area’s population. • Families already eating out may eat out more often than other families in the are. Scenario #1 is BIASED Scenario #2 is BIASED

  10. Surveys are useful, but sometimes we need to gather data from individuals in different ways.

  11. Experiment • Imposes a treatment on individuals • Collects data on their response to the treatment

  12. Observational Study • Observes individuals and measures variables without controlling the individuals or their environment in any way

  13. Examples • A researcher asks students the average number of hours they spend studying for a test to see if there is a relationship between studying and grades. • A cosmetologist wants to know whether nail polish A lasts longer than nail polish B, so she paints two sets of nails with each polish. This is an observational study, because the researcher isn’t controlling the students or applying a treatment. This is an experiment, because the cosmetologist applies a treatment to some individuals.

  14. More About Experiments • For experiments to be useful, they must be carefully thought out and designed. • A CONTROLLED EXPERIMENT sets up a control group and a treatment group so that two groups can be studied under conditions that are identical except for one variable. • A RANDOMIZED COMPARATIVE EXPERIMENT is one in which individuals are assigned to the control group or the treatment group randomly in an effort to minimize bias.

  15. Example At a local elementary school, 150 randomly chosen students were given milk at lunch for a year. 150 other randomly chosen students were given other drinks at lunch for a year. At the end of the year, students in the milk group had 22% fewer calories than the students in the other group. • Randomized Comparative Experiment • Treatment is drinking milk at lunch • Treatment group drank milk • Control group drank other beverages

  16. Suppose you want to answer this question: Does listening to an iPod™ with earphones for more than two hours a day affect a person’s hearing? • Which would be better: an experiment or an observational study? • In this case, an observational study would be best, because it wouldn’t be fair to ask a treatment group to possibly ruin its hearing if the individuals don’t already listen to music with headphones. • To be effective, randomly choose one group of people that already listens to an iPod™ with headphones for more than two hours a day. Then, randomly choose one group of people that doesn’t listen to music with headphones. • Monitor the hearing of both groups regularly and record results.

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