/*! 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

A consumer product agency tests miles per gallon for a sample of automobiles using each of four different octanes of gasoline. Which of the following is true? (A) There are four explanatory variables and one response variable. (B) There is one explanatory variable with four levels of response. (C) Miles per gallon is the only explanatory variable, but there are four response variables corresponding to the different octanes. D) There are four levels of a single explanatory variable. (E) Each explanatory level has an associated level of response.

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.

When the estrogen-blocking drug tamoxifen was first introduced to treat breast cancer, there was concern that it would cause osteoporosis as a side effect. To test this concern, cancer subjects were randomly selected and given tamoxifen, and their bone density was measured before and after treatment. Which of the following is a true statement? (A) This study was an observational study. (B) This study was a sample survey of randomly selected cancer patients. (C) This study was an experiment in which the subjects were used as their own controls. (D) With the given procedure, there cannot be a placebo effect. (E) Causation cannot be concluded without knowing the survival rates.

In a study of successes and failures in adopting Common Core standards, a random sample of high school principals will be selected from each of the 50 states. Selected individuals will be asked a series of evaluative questions. Why is stratification used here? (A) To minimize response bias (B) To minimize nonresponse bias (C) To minimize voluntary response bias (D) Because each state is roughly representative of the U.S. population as a whole (E) To obtain higher statistical precision because variability of responses within a state is likely less than variability of responses found in the overall population

To find out the average occupancy size of student-rented apartments, a researcher picks a simple random sample of 100 such apartments. Even after one follow-up visit, the interviewer is unable to make contact with anyone in 27 of these apartments. Concerned about nonresponse bias, the researcher chooses another simple random sample and instructs the interviewer to continue this procedure until contact is made with someone in a total of 100 apartments. The average occupancy size in the final 100-apartment sample is 2.78 . Is this estimate probably too low or too high? (A) Too low, because of undercoverage bias (B) Too low, because convenience samples overestimate average results (C) Too high, because of undercoverage bias (D) Too high, because convenience samples overestimate average results (E) Too high, because voluntary response samples overestimate average results
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