Draft 1: She's So Fine, My 409: Oxford Automobiles and their Underlying Values

This topic submitted by Fried, Fox, Small, Stewart, Woehr, Yon (foxem@miamioh.edu) at 2:20 pm on 10/4/00. Additions were last made on Wednesday, May 7, 2014. Section: Campbell

In the small town of Oxford, Ohio, many different cars are driven, partly due to the large college population and the fact that there is a huge amount of variety of vehicles that one can drive. All of these choices come along with them certain statements about priority. The question becomes, what priorities do people have in mind when they purchase an automobile?

This study will take a survey of many of the different cars that are in the Oxford community. What style of car is the most popular? What is the preferred color? Most importantly, what does this say about our community’s values as evidenced by what they drive?

First we can assume what people look for when purchasing a car. According to Kiplinger’s New Cars and Trucks, people consider, in no particular order, luxury, cargo space, head/leg room, horsepower, resale value, acceleration, fuel efficiency, comfort, safety and popularity. Our study is more concerned with more basic priorities rather than considerations, namely style and status versus efficiency, safety, and environmental concerns. Do people use cars to look good or get from point A to point B?

Our hypothesis is that drivers in Oxford value style and status over economy, safety and the environment. We expect to find the most popular car s to be sport-utility vehicles (SUV’s) and sports cars, with the most popular color being red.

The relevance of this experiment would be to prove a long-held stereotype that Miami students are materialistic. The results will also show that the community as a whole is rather wealthy and concerned with style.

Experimental Design & Data Collection

In our experiment, we have devised two methods of collecting data. This data will use non-random and random sampling techniques. For the non-random sampling, we will consult the Miami University Police Department and get records of all of the student cars registered with the University and parked in Detmer parking lot. We will record the style and color of the car registered. This will give us a huge starting base for our data. The records at Detmer will also give us the chance to record the cars driven by underclassmen, because University regulations require that underclassmen with cars on campus must park it at Detmer.

For the chance to record the cars driven by upperclassmen and faculty, we have devised another non-random sampling method. We will record the cars parked in the parking lots around campus at various times of the day. This will be done throughout the semester to ensure a wide variety of cars parked in a certain area. Although there will be some overlap by those who have a preferred parking space, this will aid our study by showing which cars are driven frequently. Since the Miami University community makes up two-thirds of the Oxford community, we have a way to record the majority of vehicles Oxford.
Our random sampling method serves as a way to record the cars drove in Oxford as a whole, not exclusive to the University. At various times in the day throughout the semester, pairs of people from our group will observe the cars that pass them at certain intersections in Oxford. These intersections include Patterson Avenue and High Street, Campus Avenue and High Street, and the Wendy’s located uptown. We will be in pairs of people, ensuring that every car that is seen can be recorded.

For both the non-random and random sampling method, we will use the data sheet attached to the end of this proposal, for consistency. By using these techniques, we can obtain a statistically sound database.

Methods and Materials

Based on our own observations of various car types in different parking lots on campus and in Oxford, we can conclude that our data will be statistically sound. Our statistic sheet will be given to the other groups in class so that we can get their results and incorporate that data with our own. We asked for advice focusing on Stat view, and we’ve decided to place our data within the Statview program, not only for organizational purposes, but also because of our new acquired knowledge of the function.

Since the whole class (included us) will be recording data on their own terms, the factual and true information will be given. No unbiased results should occur due to the fact that the groups as are we, will use the statistics sheet to simply record what kind of automobile they see.

We can ensure that the data collected from the other groups can be trusted based on their results. Since we have a standard statistics sheet that each group will obtain, their results should fit the questions we ask them to explore. If the data seems a bit too far-fetched, we may have to question the group and possibly disregard their results. We think each group will cooperate throughout these proposals. We will consistently show our data record weekly, and even include the weekends. In turn our results will either be consistent or have no consistency at all. We have to wait and find out!

The materials that we will use include patience, our standard statistics sheet, and the Statview program. We need to be patient as we record the data weekly, and not get bored, or discouraged if it’s hot for instance. Our statistics sheet is an important tool we need in order to collect our results for the bulk of our lab proposal. It is important for it to be clear and concise so the other groups will have an easy time gaining the results we need from various areas on and off campus. Statview will be our organizer, organizing all of our results. We are prepared to set up different graphs relating our information from our results. Stat view is a great tool and we plan to use it effectively. The other materials we will use are self explanatory, such as writing utensils, and other basic scientific tools.

Class Data Collecting

The class will also be very involved in our study. Our plan for our day conducting class will go as follows. The entire class will number off by twos. One class will participate in a group discussion about the stereotypes of Miami University students and their materialistic values. The discussion will then lead to cars, and what people consider when purchasing a car. They will discuss which cars are more efficient than others and which ones are mainly for show or style. One of our group members will make a list of the human values, and the different considerations of a car. The discussion will also include a classification session, or going over the different types of cars, and which category they go into. The other group will receive a data collecting sheet and will go to Western Drive or another assigned area and collect data by making tally marks on their sheet of each car which they will categorize and mark it according to color. (Please see our data sheet to further explain). After counting a minimum of 30 cars, the groups will then switch, and the group that started out in discussion will then receive a data-collecting sheet and will go collect data of 30 cars (preferably not the same ones). After the second discussion is completed and the second group is finished collecting data, both groups will then station themselves at the two computers in the Peer Science Center and use Statview to analyze their results and to further their understanding of our experiment. The Herbivores could then use their Statview results to come up with a general idea how our results will turn out.

In summary, the class will be asked to participate in a group discussion, collect data, and then process it through Statview. This will help our group get a general idea of how our results will turn out, and help them understand our experiment and the main ideas behind it. This is a hands-on lab for the students in our class, and we feel they will do more than only do well and complete this lab successfully. They will facilitate our group in determining what our results might be and the Statview results will be used to analyze all of our data.

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