91Ó°ÊÓ

In Exercise \(1.18,\) we ask whether experiences of parents can affect future children, and describe a study that suggests the answer is yes. A second study, described in the same reference, shows similar effects. Young female mice were assigned to either live for two weeks in an enriched environment or not. Matching what has been seen in other similar experiments, the adult mice who had been exposed to an enriched environment were smarter (in the sense that they learned how to navigate mazes faster) than the mice that did not have that experience. The other interesting result, however, was that the offspring of the mice exposed to the enriched environment were also smarter than the offspring of the other mice, even though none of the offspring were exposed to an enriched environment themselves. What are the two main variables in this study? Is each categorical or quantitative? Identify explanatory and response variables.

Step by step solution

01

Identify Main Variables

The first step in answering this question is to determine the two main variables in the study. In this case, they are the 'living conditions' and 'intelligence (speed in navigating mazes)' of the mice.

02

Classify Variables as Categorical or Quantitative

The next step is to determine whether each variable is categorical or quantitative. The 'living conditions' variable is categorical because it can be divided into two distinct categories: mice that lived in an enriched environment and mice that did not. The 'intelligence' variable is quantitative because it can be measured by how quickly the mice navigate mazes.

03

Identify Explanatory and Response Variables

The final step is to identify which of the variables is explanatory and which is the response. Here, the 'living conditions' variable is explanatory because it explains or can have an effect on the response variable. Therefore, the 'intelligence' variable is the response because it responds to or can be affected by the explanatory variable.

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.

Quantitative Variables

Quantitative variables refer to variables that are measured numerically. Their values convey specific quantities or numerical information. In our exercise, the intelligence of mice, assessed by how fast they navigate a maze, is a perfect example of a quantitative variable. This variable can be expressed using numbers, such as seconds or minutes taken by the mice to complete the maze. Quantitative variables like these are often used in data analysis because they allow researchers to apply mathematical and statistical techniques. Understanding quantitative data can help in:

• Summarizing information using measures like mean, median, or range.
• Comparing differences between groups based on averages.
• Visualizing data through graphs and charts to showcase trends or patterns.

These interpretations provide valuable insights into the study's outcomes, helping explain differences in intelligence levels influenced by different environments.

Categorical Variables

Categorical variables, unlike quantitative ones, are not numerical. Instead, they represent groups or categories. In the given exercise, the 'living conditions' of mice is a categorical variable. It consists of two distinct groups: mice living in enriched environments and those that do not. This type of variable helps researchers categorize subjects based on traits or factors that aren't inherently measured by numbers. Categorical data is crucial in scientific studies for several reasons:

• It helps identify and separate different groups within a dataset for comparison.
• It is useful for understanding frequencies or proportions, such as how many mice were in each environment.
• It aids in organizing information that has qualitative attributes, making analysis more structured.

By recognizing the nature of categorical variables, researchers can better understand how different group classifications might affect other variables in a study.

Explanatory and Response Variables

In studies, explanatory and response variables play a crucial role in understanding cause-and-effect relationships. The explanatory variable, sometimes called an independent variable, is the one that you suspect may influence the other variable. In the mouse study, the 'living conditions' variable is explanatory because it impacts the outcome. On the other hand, the response variable, also known as a dependent variable, is what researchers observe or measure as an effect. Here, the 'intelligence' of the mice, measured by maze navigation speed, is the response variable. Identifying these variables is essential for:

• Determining the direction of influence between the variables.
• Ensuring accurate data analysis and interpretation in research.
• Formulating clear hypotheses that guide experimental design.

Understanding the role of each variable type helps clarify how one factor could potentially impact another in any given study.