/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 5 In designing an experiment, bloc... [FREE SOLUTION] | 91影视

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Chapter 3: Problem 5

In designing an experiment, blocking is used (A) to reduce bias. (B) to reduce variation. (C) as a substitute for a control group. (D) as a first step in randomization. (E) to control the level of the experiment.

Short Answer

Expert verified
The correct answer is (B) to reduce variation.

Step by step solution

01

Understand the Concept of Blocking

Blocking is a technique used in the design of experiments. It involves grouping similar experimental units together to account for variability among them, thus providing more accurate results.
02

Identify the Purpose of Blocking

The main purpose of blocking is to account for and reduce variation from confounding variables. By doing so, it helps to isolate the effect of the experimental treatments.
03

Evaluate Each Answer Option

Consider each provided option in light of the purpose of blocking: (A) Reducing bias鈥擝locking does not directly reduce bias; it manages variation. (B) Reducing variation鈥擳his is correct as blocking minimizes the impact of confounding variables. (C) Substitute for a control group鈥擝locking is not used as a substitute for control groups. (D) First step in randomization鈥擝locking is not related to the process of randomization but rather complements it. (E) Control the level of the experiment鈥擳his option is too vague and unrelated to the specific purpose of blocking.
04

Select the Correct Answer

Based on the evaluations, (B) to reduce variation is the correct answer. Blocking reduces the variation from confounding variables, allowing for clearer comparison between experimental treatments.

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Key Concepts

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

blocking
Blocking is a crucial technique in experimental design. It involves grouping experimental units with similar characteristics together. For instance, in an agricultural experiment, different plots of land that have similar soil quality might be grouped or 'blocked' together. This method helps to account for variability among these units. By doing so, we can get more precise and accurate results because it minimizes the chances that external factors will skew the outcomes. In essence, blocking ensures that comparisons made within a block are fairer and more reliable. It emphasizes isolating the variability that might come from confounding sources.
reducing variation
One of the primary goals in designing an experiment is to reduce variation. Variation refers to the differences in outcomes that arise due to uncontrolled factors. By reducing this, researchers can obtain clearer and more trustworthy results. Blocking helps achieve this by accounting for and minimizing the influence of these external factors. For example, in a medical trial, patients might be blocked based on age or severity of illness. This ensures that the treatment effects observed are not clouded by these variables. The more we reduce variation, the more confidence we can have in the results showing the true effect of the experimental treatments.
confounding variables
Confounding variables are factors other than the independent variable that may affect the outcome of an experiment. They can introduce bias and make it difficult to determine the true relationship between the variables being studied. For example, in a diet study, exercise level can be a confounding variable if not properly controlled. Blocking helps mitigate the effect of confounding variables. By grouping similar units together, it allows researchers to isolate the impact of the independent variable more effectively. Moreover, it provides a clearer view of how different treatments affect the outcomes, free from the influence of other variables.
experimental treatments
Experimental treatments are the different conditions or interventions that are applied to the experimental units. For instance, in a drug trial, different dosages of a medication represent different experimental treatments. The goal is to compare the effects of these treatments to determine which is most effective. Effective experimental design, including techniques like blocking, helps ensure these comparisons are valid. By controlling variation and reducing the impact of confounding variables, researchers can make more precise and reliable comparisons between the treatments. This allows them to draw valid conclusions about the efficacy of the treatments being studied.

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Most popular questions from this chapter

School uniforms are being adopted by U.S. public schools in increasing numbers. Two possible wordings for a question on whether or not students should have to wear school uniforms are as follows: I. Many educators believe in creating a level playing field to reduce socioeconomic disparities. Do you believe that students should have to wear school uniforms? II. Many sociologists believe that students have a right to express their individuality. Do you believe that students should have to wear school uniforms? One of these questions showed that \(18 \%\) of the population favors school uniforms, while the other question showed that \(23 \%\) of the population favors school uniforms. Which question probably produced which result and why? (A) The first question probably showed \(23 \%\) of the population favors school uniforms, and the second question probably showed \(18 \%\) because of the lack of randomization in the choice of pro-uniform and antiuniform arguments as evidenced by the wording of the questions. (B) The first question probably showed \(18 \%\) and the second question probably showed \(23 \%\) because of stratification in the wording of the questions. (C) The first question probably showed \(23 \%\) and the second question probably showed \(18 \%\) because of the lack of a neutral cluster in the sample. (D) The first question probably showed \(18 \%\) and the second question probably showed \(23 \%\) because of response bias due to the wording of the questions. (E) The first question probably showed \(23 \%\) and the second question probably showed \(18 \%\) because of response bias due to the wording of the questions.

Which of the following is incorrect? (A) Blocking is to experiment design as stratification is to sampling design. (B) By controlling certain variables, blocking can make conclusions more specific. (C) The paired comparison design is a special case of blocking. (D) Blocking results in increased accuracy because the blocks have smaller size than the original group. (E) In a randomized block design, the randomization occurs within the blocks.

To evaluate their catering service with regard to culinary excellence, airline executives plan to pick a random passenger to start with and then survey every tenth passenger departing from a Beijing to San Francisco flight. Which of the following best describes the executives' sampling plan? (A) A convenience sample (B) A simple random sample (C) A stratified random sample (D) A cluster sample (E) A systematic sample

Which of the following is a true statement? (A) If bias is present in a sampling procedure, it can be overcome by dramatically increasing the sample size. (B) There is no such thing as a "bad sample." (C) Sampling techniques that use probability techniques effectively eliminate bias. (D) Convenience samples often lead to undercoverage bias. (E) Voluntary response samples often underrepresent people with strong opinions.

In a \(1927-1932\) Western Electric Company study on the effect of lighting on worker productivity, productivity increased with each increase in lighting but then also increased with every decrease in lighting. If it is assumed that the workers knew that they were being observed and that a study was in progress, this is an example of (A) the effect of a treatment unit. (B) the placebo effect. (C) the control group effect. (D) sampling error. (E) voluntary response bias.
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