Question

Based on observing more than 400 drivers in the Atlanta area, two investigators at Georgia State University concluded that people exiting parking spaces did so more slowly when a driver in another car was waiting for the space than when no one was waiting ("Territorial Defense in Parking Lots: Retaliation Against Waiting Drivers," Journal of Applied Social Psychology [1997]: \(821-834\) ). Describe how you might design an experiment to determine whether this phenomenon is true for your city. What is the response variable? What are some extraneous factors and how does your design control for them?

Short answer

The response variable is the time it takes for a person to exit a parking space. Extraneous factors could include the size of the parking space, busyness of the parking lot, time of day, driver's skill levels, and presence of passengers in the car. Control for these by selecting similar parking lots and observing at similar times of the day. As for driver's skills and presence of passengers, assume these are equally likely among all drivers, thus they will balance out in the larger sample.

Step-by-step solution

Understanding the Phenomenon

There's a claim that drivers exit parking spaces more slowly when another car is waiting than when there's nobody waiting. Here, we are going to create a design that will help to investigate this claim in a different city.

Designing the Experiment

To replicate this experiment in your city, a proper method would be Observational Study. One would need to select multiple parking lots in various locations around the city. Over several days and different times, observe drivers exiting parking spaces. Record two things: how long it takes for them to exit the parking space, and whether there was another driver waiting for the space or not.

Identifying the Response Variable

The response variable is the amount of time it takes for a person to exit a parking space. This is what we're interested in and is the variable we're studying to see if the behavior of drivers being observed influences it.

Identifying Extraneous Factors

Extraneous factors may include: the size of the parking space, how busy the parking lot is, the time of day, the driver's skills or if there are passengers in the car.

Controlling for Extraneous Factors

To control these factors, select parking lots that are similar in size and in busy parts of town, and do the observation at similar times of day. It might be hard to control for the driver's skills and if there are passengers in the car without interacting with the drivers, which might change their behavior and bias the results. But we can assume that these factors are equally likely for all drivers, thus balancing out in the larger sample.

Key concepts

Observational Study

An observational study serves as an effective approach to capturing behavior in a natural setting without any interference by the researcher. In the context of parking lots and waiting drivers, this methodology fits perfectly. You would monitor over 400 drivers, akin to the Georgia State University investigation, and note their habits without intervening.

Unlike an experimental design where variables are manipulated, observational studies merely involve watching and recording events as they unfold. This means in your city, you would select various parking lots and discreetly observe drivers as they leave their parking spaces, ensuring your presence does not influence their behavior. It's critical to randomly choose different periods and times of the day to avoid biases like day versus night-time driving behaviors or weekday versus weekend patterns.

Response Variable

In statistics, a response variable is the particular quantity that you're trying to measure or understand in an experiment or study. For your parking lot investigation, the response variable is the duration it takes for a driver to exit a parking space.

This measurement ought to be as accurate as possible, and you could use a stopwatch or even video recordings to gather this data. By concentrating observations on this specific metric, we aim to determine if the presence of another waiting driver influences this timeframe, which is the core question in this behavioral study.

Controlling Extraneous Factors

Extraneous factors can significantly affect the outcome of a study. These are variables other than the response variable that could influence the results. To manage these factors in our parking lot study, we need to establish controls to prevent them from skewing the findings.

For instance, the size of the parking space or how busy the lot is can affect exit time. You could choose lots with spaces of similar dimensions and comparable traffic levels. Observing at consistent times of the day helps to control for variations in daily parking lot activity. Although it's challenging to account for driver skill or presence of passengers, assuming a large enough sample, these factors should randomly distribute across the observed instances, minimizing their impact on the study's conclusion.

Behavioral Study in Statistics

Behavioral studies in statistics focus on understanding the actions and reactions of individuals in response to various stimuli or situations. In the case of the parking lot study, we're interested in the behavioral response of drivers exiting spaces with and without an observer waiting.

It's essential to approach this study with a clear operational definition of 'exiting time' and consistent observational techniques to ensure data integrity. We would be carefully looking for patterns or changes in the drivers' behaviors under the two different conditions. The collected data would then undergo statistical analysis to determine if a significant difference exists in the exit times correlating to the presence of a waiting driver. This type of analysis helps us understand human behavior in real-world settings, contributing valuable insights into how we interact with our environment and each other.