What is beautiful?By: Rachael Bradford, Sean Christiansen, Karla Diaz, Veronica Hayes, & James Mitchell

Many people have their own interpretation of what they find beautiful. Some people find the tall, dark, and handsome man attractive. Some find that young, long blonde-haired woman attractive. Others may find that the intelligence of a scholar or the older sophisticated woman attractive. What is beautiful to you?

As a group, we were interested to see how much value an individual placed on physical beauty, taking into consideration age, gender, and education level of the respondent to see if it had any influence on how they portrayed beauty in another individual. We conducted an observational survey which asked respondents to select (on a sliding scale) who they believed was attractive from pictures of 3 different individuals. We started out by choosing to use a survey site called “Survey Monkey” to help set up the actual survey. We first selected 3 images to be used for the survey questions. One picture was of a young Audrey Hepburn. The second image was of a young Afghani woman. The last picture was of a middle aged Afghani man.

The survey was designed, deployed and analyzed from an online survey. Most surveys were conducted due to contact through facebook or email. The survey was open from Monday, April 8 th 2013 to Friday, April 12th.

Our survey consisted of 7 questions:

1. On a scale of 1 to 5 where 1 means not at all and 5 means very much, how much value do you place on physical beauty in another person?

2. Please rate the person in the previous image (Audrey) on a scale from 1 to 10, where 1 means Not Attractive/Beautiful At All and 10 means Very Attractive/Beautiful.

3. Please rate the person in the previous image (Afghani woman) on a scale from 1 to 10, where 1 means Not Attractive/Beautiful At All and 10 means Very Attractive/Beautiful.

4. Please rate the person in the previous image (Afghani man) on a scale from 1 to 10, where 1 means Not Attractive/Beautiful At All and 10 means Very Attractive/Beautiful.

5. What is the highest level of education you have completed?6. What is your age?7. What is your gender?

Though we collected data on multiple questions, we decided for the sake of this presentation and data analytics to focus on the first question “ On a scale of 1 to 5 where 1 means not at all and 5 means very much, how much value do you place on physical beauty in another person?”. Frequencies and histograms of all questions are listed later in this document.

In order to test our hypotheses, we used frequency tables, histograms, T-distributions and the chi-squared test to analyze the results of our survey.

We used the frequency tables and histograms for each question to indicate the proportion of observations from each respondent in our survey of 57 individuals (of which most answered all questions presented). Even though both the frequency tables and the histograms have similar data, we wanted to use histograms for a better visual display of our collected data compared to a normal curve.

We used T-distributions to test in depth the 3 variables we were most interested in. These variables were education, age and gender.

Our hypotheses were as follows:

-Education: Those with more education will place a lower value on physical beauty in another person.

-Age: Younger respondents will place a higher value on physical beauty in another person.

-Gender: Female respondents will place a higher value on physical beauty in another person.

Results of the survey data versus our hypotheses:

-Education:

Hypothesis: Those with more education will place a lower value on physical beauty in another person.

Results: Those with more education placed a higher value on physical beauty.

-Age:

Hypothesis: Younger respondents will place a higher value on physical beauty in another person.

Results: Younger respondents placed a lower value on physical beauty.

-Gender:

Hypothesis: Female respondents will place a higher value on physical beauty in another person.

Results: Female respondents placed a lower value on physical beauty.

Looking at this particular set of respondents, the survey results have disproven every one of our hypotheses, demonstrating the effectiveness of statistically analyzing data as opposed to making any type of assumption.

We used the chi-squared test to compare the observed and expected counts and to determine if we should accept or reject the null hypothesis. These charts are listed further in depth later on in this document. After running the chi-squared tests, we determined that the p-value is smaller than the chi-square, so we rejected the null hypothesis for each test.

In conducting our study, we did observe that there were areas for improvement if another survey was run. First we noticed that using the free survey site “Survey Monkey” came with a few limitations in itself. Survey Monkey’s free option has a 10 question limit (including graphics), a 100 survey limit, no question rotations, and no conditional logic.

Also, we deployed the survey via facebook and email so data was collected from those who had access to the computer and internet. The survey was an observational study, which used a self-selected convenience sample to collect results. Due to the survey being deployed via facebook, the average age of data collected was 25-35 years of age; therefore this is not representative of the population. A sampling bias may be present (ie: those who chose to opt in versus opt out as well as those we were unable to reach due to no computer or internet access). Also, there may be under coverage (the survey data skews towards a younger age group).

Maybe if we had more time to conduct other survey methods besides facebook and email, we may have had a bigger sample group than the 57 individuals who chose to take the survey.

Works Cited

http://www.surveymonkey.com/

http://www.wikipedia.org/

http://creativecommons.org/

Sullivan III, M. (2010, 2007,2004). Statistics Informed Decisions Using Data (3rd ed.). New Jersey: Pearson Education, Inc.