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Coffee stations in offices often just ask users to leave money in a tray to pay for their coffee, but many people cheat. Researchers at Newcastle University replaced the picture of flowers on the wall behind the coffee station with a picture of staring eyes. They found that the average contribution increased significantly above the well-established standard when people felt they were being watched, even though the eyes were patently not real. (NY Times \(12 / 10 / 06)\) a) Was this a survey, an observational study, or an experiment? How can we tell? b) Identify the variables. c) What does "increased significantly" mean in a statistical sense? 7-20. What's the design? Read each brief report of statistical research, and identify a) whether it was an observational study or an experiment. If it was an observational study, identify (if possible) b) whether it was retrospective or prospective. c) the subjects studied and how they were selected.

Short Answer

Expert verified
a) Experiment; b) Independent: picture, Dependent: contribution; c) Statistically significant increase (p < 0.05).

Step by step solution

01

Determine the Type of Study (Survey, Observational Study, or Experiment)

To understand whether this research is a survey, observational study, or experiment, note that the setup involved the manipulation of an environment—specifically, replacing a picture of flowers with eyes to observe the change in contributions. This indicates it is an experiment because there is a direct intervention to observe changes in behavior.
02

Identification of Variables

The variables in this study include the independent and dependent variables. The independent variable is the picture behind the coffee station (flowers vs. eyes), while the dependent variable is the average monetary contribution made by coffee station users.
03

Understanding 'Increased Significantly' in Statistics

Statistically, 'increased significantly' means that the observed increase in contributions is unlikely to have occurred by chance alone. This usually means that a statistical test has been conducted showing the increase is statistically significant, typically with a p-value less than 0.05.
04

Classify the Research Design (Observational Study or Experiment)

From the earlier analysis, we confirmed this is an experiment due to the manipulation of the environment (switching pictures) aimed at inducing changes in participant behavior. There is no retrospective or prospective observation of participants, but rather directly influencing their environment to study the outcome.
05

Identify Subjects and Their Selection

The subjects of this study were the individuals using the coffee station. The selection process seems to be naturalistic, implying all users of the coffee station during the study period are considered subjects, likely not involving a specific selection process beyond their decision to visit the station.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Observational Study
In an observational study, researchers observe subjects without intervening or altering the environment. The goal is to gather data that reflects natural conditions. This type of study is often used when experimenting would be unethical or impractical.
For example, imagine a study that involves observing how people behave in response to a public announcement. The researchers simply watch and record how different participants react without influencing the situation.
  • Non-intrusive: Researchers do not interfere with the situation.
  • Natural setting: Allows for the collection of real-world data.
  • Complexity: More variables may be present, making analysis challenging.
Observational studies are helpful in exploring a topic, but they can't conclusively establish a cause-and-effect relationship.
Independent Variable
The independent variable is the one that researchers manipulate to see how it affects other variables, specifically the dependent variables. It serves as the cause side of the cause-and-effect relationship in an experiment.
In the coffee station study, the independent variable was the picture behind the station—either flowers or eyes. Researchers altered this aspect of the environment to observe its impact on the contributions.
  • Control: This is the factor researchers change to observe reactions.
  • Cause-and-effect exploration: Enables a study to determine if changes cause certain outcomes.
Identifying the independent variable is crucial for designing an experiment, as it establishes the parameters for examination.
Dependent Variable
The dependent variable is what researchers measure in an experiment. It's the result or outcome that may change due to variations in the independent variable. Essentially, it's the effect side of the relationship.
In the context of the coffee station experiment, the dependent variable was the average monetary contribution made by users. Researchers wanted to see if changing the picture would alter how much money people left.
  • Measurement: Observed changes are recorded and analyzed.
  • Response: The variable that exhibits any changes is the response to manipulations.
Understanding dependent variables helps interpret the results of an experiment and determines if the independent variable had any effect.
Statistical Significance
Statistical significance indicates whether the results of an experiment are likely due to chance or if they are truly meaningful. It is a mathematical measure, often expressed with a p-value, that determines the likelihood of an observed effect. A p-value less than 0.05 typically denotes statistical significance.
In the Newcastle University coffee station experiment, researchers found that contributions "increased significantly." This suggests that the change from flowers to eyes was unlikely by chance and truly affected people's behavior.
  • Reliability: Assurance that results are credible and not random.
  • P-value: A statistical measure that helps in assessing the significance.
  • Decision-making: Crucial for determining the validity of experimental findings.
Understanding statistical significance helps assess how trustworthy the data is and supports the validity of the experimental results.

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Most popular questions from this chapter

Researchers studied the herb black cohosh as a treatment for hot flashes caused by menopause. They randomly assigned 351 women aged 45 to 55 who reported at least two hot flashes a day to one of five groups: (1) black cohosh, (2) a multiherb supplement with black cohosh, (3) the multiherb supplement plus advice to consume more soy foods, (4) estrogen replacement therapy, or (5) receive a placebo. After a year, only the women given estrogen replacement therapy had symptoms different from those of the placebo group. [Annals of Internal Medicine \(145: 12,869-897]\) a) What kind of study was this? b) Is that an appropriate choice for this problem? c) Who were the subjects? d) Identify the treatment and response variables.

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