91Ó°ÊÓ

A utility company was interested in knowing if agricultural customers would use less electricity during peak hours if their rates were different during those hours. (Agricultural energy use is substantial, for things like irrigation, lighting, wind turbines to reduce frost damage, and so on.) Customers who volunteered for the study were randomly assigned to continue to get standard rates or to receive the time-of-day rate structure. Special meters were attached that recorded usage during peak and off-peak hours, which the customers could read. The technician who read the meter did not know what rate structure each customer had. a. What was the explanatory variable in this experiment? b. What was the response variable in this experiment? c. Was this experiment single-blind, double-blind, or neither? Explain. d. Did this experiment use matched pairs, blocks, or neither? Explain.

Step by step solution

01

Identify the Explanatory Variable

In an experiment, the explanatory variable is the one that the experimenter manipulates to observe its effect on the response variable. Here, the utility company manipulates the rate structure of electricity (standard rates vs. time-of-day rates) to observe its effect on electricity usage. Therefore, the explanatory variable is the rate structure.

02

Identify the Response Variable

The response variable is what the experimenter measures to see the effect of changes in the explanatory variable. In this case, the utility company measures the electricity usage during peak and off-peak hours to see if the rate structure affects it. Therefore, the response variable is the electricity usage during these periods.

03

Determine if the Experiment is Blind

In experimental design, blinding is used to prevent bias. A single-blind experiment is when the subjects do not know which treatment they receive, while a double-blind experiment is when neither the subjects nor the experimenters know. Here, the technicians do not know the rate structure each customer received, but there is no indication that the customers are unaware. Hence, this experiment is single-blind.

04

Identify if Matched Pairs or Blocks are Used

Matched pairs involve pairing similar subjects and giving them different treatments, while blocks involve grouping subjects with similar characteristics. In this experiment, there is no mention of specific pairs or grouping based on characteristics; customers were randomly assigned the rate structures. Thus, neither matched pairs nor blocks are used.

Unlock Step-by-Step Solutions & Ace Your Exams!

• Full Textbook Solutions

  Get detailed explanations and key concepts

• Unlimited Al creation

  Al flashcards, explanations, exams and more...

• Ads-free access

  To over 500 millions flashcards

• Money-back guarantee

  We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

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

Explanatory Variable

In experimental design, the explanatory variable is the factor that researchers manipulate to determine if it has an effect on the outcome of interest. In our example with the utility company, the explanatory variable is the rate structure for electricity.

The company sets two different pricing models: standard rates and time-of-day rates. By changing this specific condition, they aim to see if customers will adjust their electricity consumption, mainly during peak hours.

Selecting the correct explanatory variable is key as it helps in setting the foundation of the experiment, ensuring that the data collected corresponds to the changes being tested.

Response Variable

The response variable is the outcome that is measured in an experiment, reflecting the effect of the explanatory variable's manipulation. In the utility company's study, the response variable is the electricity usage recorded during peak and off-peak hours.

This measurement tells us how the different rate structures influence electricity consumption. By focusing on usage data, the company can gather evidence on whether or not their pricing strategies are effective at encouraging reduced power usage during these critical times.

• This direct relationship helps in drawing conclusions.
• It shows how changing the explanatory variable (rate structure) affects customer behavior.

Single-Blind Experiment

In experimental designs like the one described here, blinding is an essential element. It helps reduce bias and ensures that the results are more reliable. A single-blind experiment means that the subjects or the researchers (but not both) are unaware of the treatment being administered.

For the utility company's study, the experiment is single-blind because the technicians who read the meters do not know which customers are on the standard rates or the time-of-day structure.

• This prevents the technician's potential biases from impacting data collection.
• However, the customers themselves are aware of their rate structure.

This keeps the measurement process objective as far as the technician's assessments are concerned.

Random Assignment

Random assignment plays a crucial role in ensuring that experimental groups are equivalent at the start. It is the process by which participants in an experiment are assigned to different treatments by random methods, thereby eliminating choice bias.

In this particular experiment, the agricultural customers who volunteered for the study were randomly assigned to continue receiving the standard rates or to be part of the group with the time-of-day rates. This randomization:

• Ensures each group is comparable at the beginning.
• Minimizes potential pre-existing differences within the groups.
• Enhances the validity and reliability of the results.

By using random assignment, the utility company could make stronger inferences about the effect of their rate structures on electricity usage.