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Chapter 4: Problem 51

Identify the experimental units, the explanatory and response variables, and the treatments. Ability to grow in shade may help pines found in the dry forests of Arizona to resist drought. How well do these pines grow in shade? Investigators planted pine seedlings in a greenhouse in either full light, light reduced to \(25 \%\) of normal by shade cloth, or light reduced to \(5 \%\) of normal. At the end of the study, they dried the young trees and weighed them.

Short Answer

Expert verified
Units: Pine seedlings; Explanatory: Light level; Response: Biomass; Treatments: Full light, 25% light, 5% light.

Step by step solution

01

Identify the Experimental Units

The experimental units are the subjects or objects the experiment is conducted on. In this case, the experimental units are the pine seedlings because the study observes the growth of these seedlings under different lighting conditions.
02

Determine the Explanatory Variables

The explanatory variable, also known as an independent variable, is what the researcher manipulates to observe its effect on the response variable. Here, the explanatory variable is the level of light exposure: full light, light reduced to 25% of normal, and light reduced to 5% of normal.
03

Identify the Response Variables

The response variable, or dependent variable, is what the researcher measures to evaluate the effect of the explanatory variable. In this experiment, the response variable is the biomass of the pine seedlings, which is measured by drying and weighing the young trees.
04

Recognize the Treatments

Treatments refer to the different conditions applied to the experimental units. Each level of light exposure acts as a different treatment in this experiment. Therefore, there are three treatments: full light, 25% light, and 5% light.

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Key Concepts

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

Explanatory Variable
In an experiment, the explanatory variable is like the "input" the researchers manipulate to see if it causes any change. Think of it as the cause in a cause-and-effect relationship. In our pine seedling study, light exposure is the explanatory variable. The researchers are changing the amount of light each seedling gets to determine how it affects their growth.
  • Full light
  • 25% of normal light
  • 5% of normal light
Each of these light conditions represents a different version or "level" of the explanatory variable. By observing the seedlings under different lighting, researchers can understand how much light impacts growth.
Response Variable
The response variable is the outcome researchers are interested in measuring. It鈥檚 the "effect" part of the cause-and-effect equation. In our example with pine seedlings, the response variable is growth, specifically measured by drying and weighing the biomass of the seedlings.
This means researchers are not just randomly interested in light levels. They want to know how these light levels affect growth.
  • The more the seedlings weigh, the more they grew
  • A change in biomass indicates the effects of the light exposure treatments
This measurable result provides insight into how environmental conditions influence the seedlings.
Experimental Units
The term "experimental units" refers to the individual elements or entities that the experiment is performed on. These are essentially the subjects of the study. In this case, each pine seedling serves as an experimental unit. These are the living entities experiencing the different levels of light conditions set by the researchers.
When you imagine each seedling, think of it as an individual participant in the study.
  • Each seedling is treated separately.
  • They provide separate data points for analysis.
Identifying the experimental units is crucial because it helps define the scope and scale of the experiment. It determines what exactly the researchers are trying to analyze.
Treatments
In scientific experiments, treatments are the different conditions applied to the experimental units. These are set up to test the effect of the explanatory variable. In our example, each level of light exposure is considered a distinct treatment. So, we have three specific treatments here:
  • Full light exposure
  • 25% of normal light exposure
  • 5% of normal light exposure
By implementing these different treatments, researchers can draw conclusions on the effect of varying light conditions on the growth of pine seedlings. Each treatment allows researchers to model different scenarios. This helps in understanding the optimal conditions necessary for resilience against drought.

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Most popular questions from this chapter

A University of Helsinki (Finland) study wanted to determine if chocolate consumption during pregnancy had an effect on infant temperament at age 6 months. Researchers began by asking 305 healthy pregnant women to report their chocolate consumption. Six months after birth, the researchers asked mothers to rate their infants' temperament, including smiling, laughter, and fear. The babies born to women who had been eating chocolate daily during pregnancy were found to be more active and "positively reactive"-a measure that the investigators said encompasses traits like smiling and laughter. \({ }^{32}\) (a) Was this an observational study or an experiment? Justify your answer. (b) What are the explanatory and response variables? (c) Does this study show that eating chocolate regularly during pregnancy helps produce infants with good temperament? Explain.

Researchers on aging proposed to investigate the effect of supplemental health services on the quality of life of older people. Eligible patients on the rolls of a large medical clinic were to be randomly assigned to treatment and control groups. The treatment group would be offered hearing aids, dentures, transportation, and other services not available without charge to the control group. The review board felt that providing these services to some but not other persons in the same institution raised ethical questions. Do you agree?

A hotel has 30 floors with 40 rooms per floor. The rooms on one side of the hotel face the water, while rooms on the other side face a golf course. There is an extra charge for the rooms with a water view. The hotel manager wants to survey 120 guests who stayed at the hotel during a convention about their overall satisfaction with the property. (a) Explain why choosing a stratified random sample might be preferable to an SRS in this case. What would you use as strata? (b) Why might a cluster sample be a simpler option? What would you use as clusters?

At a party there are 30 students over age 21 and 20 students under age 21 . You choose at random 3 of those over 21 and scparately choose at random 2 of those under 21 to interview about attitudes toward alcohol. You have given every student at the party the same chance to be interviewed. Why is your sample not an SRS?

Suppose that \(35 \%\) of the registered voters in a state are registered as Republicans, \(40 \%\) as Democrats, and \(25 \%\) as Independents. A newspaper wants to select a sample of 1000 registered voters to predict the outcome of the next election. If they randomly select 350 Republicans, randomly select 400 Democrats, and randomly select 250 lndependents, did this sampling procedure result in a simple randon sanple of registered voters from this district? (a) Yes, because each registered voter had the same chance of being chosen. (b) Yes, because random chance was involved. (c) No, because not all registered voters had the same chance of being chosen. (d) No, because there were a different number of registered voters selected from each party. (e) No, because not all possible groups of 1000 registered voters had the same chance of being chosen.
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