Grouping together similar experimental units and then randomly assigning the experimental units within each group to a treatment is called .
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
1. Intro to Stats and Collecting Data
Intro to Stats
Problem 1.6.8b
Textbook Question
"Alcohol Dependence To determine if topiramate is a safe and effective treatment for alcohol dependence, researchers conducted a 14-week trial of 371 men and women aged 18 to 65 years diagnosed with alcohol dependence. In this double-blind, randomized, placebo-controlled experiment, subjects were randomly given either 300 milligrams (mg) of topiramate (183 subjects) or a placebo (188 subjects) daily, along with a weekly compliance enhancement intervention. The variable used to determine the effectiveness of the treatment was self-reported percentage of heavy drinking days. Results indicated that topiramate was more effective than placebo at reducing the percentage of heavy drinking days. The researchers concluded that topiramate is a promising treatment for alcohol dependence. Source: Bankole A. Johnson, Norman Rosenthal, et al. “Topiramate for Treating Alcohol Dependence: A Randomized Controlled Trial,” Journal of the American Medical Association, 298(14):1641–1651, 2007.
What does it mean for the experiment to be double-blind? Why do you think it is necessary for the experiment to be double-blind?"
Verified step by step guidance1
Understand the term 'double-blind' in the context of an experiment: it means that neither the participants nor the researchers administering the treatment know who is receiving the actual treatment (topiramate) and who is receiving the placebo.
Recognize that this design helps to prevent bias in the experiment. If participants knew which group they were in, their behavior or reporting might be influenced by their expectations (placebo effect).
Similarly, if researchers knew which participants were receiving the treatment, their observations or interactions could be unintentionally biased, affecting the study's objectivity.
By keeping both parties 'blind,' the experiment ensures that the differences in outcomes (such as the percentage of heavy drinking days) are more likely due to the treatment itself rather than psychological or observational biases.
Therefore, the double-blind design is necessary to increase the reliability and validity of the experiment's conclusions about the effectiveness of topiramate for alcohol dependence.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Double-Blind Experiment
A double-blind experiment is a study design where neither the participants nor the researchers know who is receiving the treatment or the placebo. This prevents bias in treatment administration and assessment of outcomes, ensuring that expectations do not influence the results.
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Randomization
Randomization is the process of assigning participants to different groups by chance, reducing selection bias. It helps ensure that groups are comparable at the start of the experiment, so differences in outcomes can be attributed to the treatment rather than other factors.
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Placebo Control
A placebo control group receives an inactive substance to compare against the treatment group. This helps isolate the treatment's true effect by accounting for the placebo effect, where participants may improve simply because they believe they are being treated.
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