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Marijuana and work. How does smoking marijuana affect willingness to work? Canadian researchers persuaded young adult men who used marijuana to live for 98 days in a "planned environment." The men earned money by weaving belts. They used their earnings to pay for meals and other consumption and could keep any money left over. One group smoked two potent marijuana cigarettes every evening. The other group smoked two weak marijuana cigarettes. All subjects could buy more cigarettes but were given strong or weak cigarettes, depending on their group. Did the weak and strong groups differ in work output and eamings? 29 (a) Outline the design of the experiment using 20 subjects with 10 assigned to each group. (b) Here are the names of the 20 subjects. Use software or Table B at line 126 to carry out the randomization your design requires. Abel Fleming Mani Scannell Aeffner Fritz Mattos Stout Birkel Giriunas Reíchert Williams Bower Kennedy Riddle Wilso DeVore Lamone Sawant Worbis (c) Do you think this can be run as a double-blind experiment? Explain.

Step by step solution

01

Design the Experiment

The experiment involves assigning 20 young adult men, who all regularly use marijuana, into two groups of 10. Each group will live in a controlled environment for 98 days. One group will smoke two potent marijuana cigarettes every evening, and the other will smoke two weak marijuana cigarettes. Performance is measured by the number of belts woven and earnings kept after expenses.

02

Random Assignment of Subjects

To randomly assign subjects, you can use software or a random number table to ensure each subject has an equal chance of being in either group. For example, writing each subject's name on a slip of paper, then drawing them one by one to assign them alternately to the strong or weak marijuana cigarette group achieves randomization.

03

Review of Table B for Randomization

Using table B, particularly line 126, each subject is matched with a number and placed into groups. Typically, numbers can be assigned serially to make selection easier. Once two teams are created, the assignments ensure that each set has unbiased selection.

04

Double-blind Setup Feasibility

A double-blind experiment involves neither the subjects nor the investigators knowing which group receives the potent cigarettes. This might be challenging, as the difference between weak and strong marijuana may be perceivable by the subjects due to its effects. However, if possible to make indistinct and measure indirect effects, it could qualify as double-blind.

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Key Concepts

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

Random Assignment

Random assignment is a crucial part of experimental design to ensure that the results are not biased. In this marijuana study, 20 subjects need to be divided into two groups of 10.
The groups should be equivalent in all respects except for the treatment they receive. In this case, one group receives potent marijuana cigarettes while the other receives weaker ones.
To achieve random assignment, you can use different methods such as:

• Software that generates random assignments
• Random number tables
• Drawing names from a hat

The main goal is to give every subject an equal chance of being assigned to any group. This reduces bias and helps ensure the differences in outcomes can be attributed to the marijuana strength rather than pre-existing differences between individuals.
By mixing the participants randomly, any variability between them is evenly distributed between the two groups, enhancing the validity of the experiment.

Double-blind Experiment

A double-blind experiment is designed so that neither the participants nor the researchers know which group receives the potent treatment. This method aims to minimize bias and influence in experimental outcomes. However, in the study of marijuana effects on productivity, conducting a double-blind experiment can be challenging.
Participants might easily discern the effects of strong versus weak marijuana due to noticeable differences in potency. These perceptible differences can unintentionally inform them of their group assignment. Despite these challenges, researchers can strive for a level of blinding by disguising other aspects of the study.
They might focus on:

• Masking appearance, labeling, and administration process of cigarettes
• Measuring indirect outcomes that are less observable by participants

This experimentation strategy is pivotal for removing observer and participant bias, as knowing which treatment is being administered could sway participants' behavior and outcomes.

Controlled Environment

A controlled environment is essential for maintaining consistency during an experiment. In this exercise, participants were placed in a "planned environment" where all aspects except the treatment they received were controlled. This approach limits external variables that could affect outcomes and ensures that any observed changes in output and earnings can be attributed more confidently to the treatment, i.e., the strength of the marijuana cigarettes.
Some key aspects of a controlled environment include:

• All participants living in the same setting for an equal duration (98 days in this study)
• Regulating diet and daily routines to ensure they remain consistent
• Providing equal access to resources, like additional cigarettes, with specific rules about their use

By controlling these factors, researchers can focus on the key variable they wish to test, here being the effect of marijuana potency on work output. This control strengthens the reliability of the conclusions drawn from the study.

Statistics in Research

In experimental research like the study of marijuana effects on labor willingness, statistics plays a pivotal role in analyzing data and drawing conclusions. Researchers use statistical tools to determine whether observed differences between the groups are significant and not due to random chance.
Some important statistical concepts include:

• Descriptive Statistics: Summarize and describe the features of data, like mean number of belts woven and earnings retained.
• Inferential Statistics: Used to make inferences or predictions about a larger population based on the sample data.
• Significance Testing: Determines if the difference in output between the two groups is statistically significant.

These statistical measures are crucial as they help researchers validate their hypotheses about the effects of marijuana potency. Well-applied statistics ensure the findings are robust and generalizable, making them invaluable tools in experimental research.