Psychology 241

Non-Experimental Research Project

Looking for Love in the Personals

 

For this project, you will investigate an assigned topic using non-experimental (observational) methods.  You will turn in a paper in APA format describing your investigation and its results.  In addition to the final draft of the paper, you will also turn in a research proposal (consisting primarily of an outline of your proposed methods for the study) about four weeks before the final paper is due, and a full write-up of your method section along with an outline of the results section about 2 weeks before the final paper is due.  The project will be worth 150 points – 25 points each for the two intermediate assignments and 100 points for the final paper.

 

You are encouraged (but not required) to work with a partner on this project.  If you do choose to work with a partner, you must both contribute to all stages of the assignment, and must both sign all submitted work to attest that you contributed equally to producing it.  If you choose not to work with a partner, you may do the project on your own.

 

Topic: Gender differences in mate selection strategies

 

What do men and women look for in a potential mate?  A prominent social psychological theory says that men and women both look for partners whose desirability matches their own, in a sort of bargaining situation (Harrison & Saeed, 1977).  In other words, you will generally seek out someone of about equal attractiveness as yourself, and if you seek someone more attractive than yourself you generally have some other quality to offer in return to make up the difference (such as wealth, social status, etc.). 

 

Evolutionary theory, however, suggests that men look for very different things than women do.  Because women invest nine months in gestation and then several more years in nursing, they are making a large commitment of resources – much more so than the male.  Because resources were scarce in the environment in which humans evolved, women should have evolved adaptations that lead them to prefer men who are willing and able to provide resources for them.  Men, on the other hand, should look for signs of youth in a mate.  Because women’s fertility declines with age, men in the ancestral environment who did not prefer younger women did not leave as many descendents.

 

Evolutionary theory, then, suggests a number of hypotheses about mating strategies:

 

Women (more than men) will seek:

·        Partners with resources

·        Older partners (because they tend to have more resources)

·        Partners who show willingness to invest resources in them

 

Men (more than women) will seek:

·        Younger partners (because fertility in women declines more with age)

·        Physically attractive partners (because the things that are considered beautiful in women are signs of youth and fertility)

·        Short-term or extramarital affairs (because reproductive success for men depends on the number of offspring they produce more than for women)

 

Women (more than men) will offer:

·        Their attractiveness

·        Their youthfulness and/or healthy lifestyle

 

Men (more than women) will offer:

·        Their resources

·        Their willingness to invest resources

 

References

 

Buss, D. M., & Barnes, M. F. (1986). Preferences in human mate selection.  Journal of Personality and Social Psychology, 50, 559-570.

Harrison, A. A., & Saeed, L. (1977). Let's make a deal: An analysis of revelations and stipulations in lonely hearts advertisements.  Journal of Personality and Social Psychology, 35, 257-264.

 

 

 

Assignment:  Design and carry out a study testing some of these hypotheses

 

·        The study must be observational, using published personal ads as the sole source of data.

·        A research proposal must be submitted by the due date in the syllabus (25 points).

·        A revision of the research plan in response to the instructors' comments, including a complete draft (not an outline) of the Method section and an outline of the proposed analyses must be submitted by the “revised proposal” due date in the syllabus (25 points).

·        The study must be completed and written up in APA style by the due date in the syllabus (100 points).

·        Separate instructions are included for each of the three assignments that must be turned in:  the Research Proposal, the Revised Research Proposal, and the Final Paper.

·        The previous draft (with the grader’s comments on it) must be turned in with each succeeding draft.

 

 

Research Proposal (First Submission)

 

Assignment:  In the research proposal, you will do each of the following:

 

  1. Title Page.   Title, author names, course number, and date, all centered and placed appropriately near the middle of the page.  In the lower left, list a “Running head” – a shortened version of the title that will appear on the top right corner of each page along with the page number. 
  2. "Introduction."  Specify exactly which hypothesis or hypotheses you will test in your study. This section should be untitled and should be at the beginning of your proposal.
  3. "Method."  Provide an outline of your proposed method section (title it "Method").  Include the following information under the appropriate subheadings:
    1. Subjects - What type of people placing ads will you consider?  All ads?  Only heterosexuals?  Explain the reasons for your decisions.
    2. Materials – Where will you find the ads that will provide your data, and how will you select your sample of ads?
    3. Design – What will be your independent and dependent variables?  (Be sure to specify exactly how they will be operationalized.)
    4. Procedure – describe the exact protocol you will use to conduct the study:

                                                               i.      What procedure will you use to collect the ads?

                                                             ii.      Content Analysis Protocol – How will you code the data?  Describe your plan for doing content analysis.  What rules will you apply when you look at the ads to determine the values you assign to your variables?  For example, if your DV is “whether the ad placer seeks an attractive partner,” how will you decide whether an ad should be coded as “yes” or “no” for that variable?  You must specify whether you will code for manifest or latent content and what specific rules coders will follow to do the coding.

  1. "Results."  Briefly say what means or proportions from your data you will compare and what your hypothesis predicts about them, or what other comparison or relationship you will test.  Label this section "Results" and place it immediately after the "Method" section.  Also tell how many coders you will have, and how you will determine whether your content analysis protocol is reliable (such as by reporting inter-rater agreement rates). 
  2. "Appendices".  Provide a copy of each of the following items in separate appendices.  Label them "Appendix A: Content Analysis Protocol,” “Appendix B: Data Summary Sheet," and "Appendix C: Coding Guide," and place them after the references list in the final paper, and before the tables and figures.  The required and optional appendices are as follows.  Note that the first one you include should be titled “Appendix A,” the second “Appendix B” and so on, along with a descriptive phrase identifying what is in the appendix (“Content Analysis Protocol,” “Data Summary Sheet” etc.).
    1. Data Sheet - sheets on which you record raw data from the ads, along with identifying labels and some initial ratings or notes (optional – you do not have to include this)
    2. Content Analysis Protocol - the rules your raters will use to analyze the content of the ads and record values for your independent and dependent variables. (required)
    3. Data Summary Sheet - a matrix containing all the data, with columns labeled by variables (independent variables, dependent variables, and identifying labels such as ad number) and one row for each observation (in this case, probably one row per ad).  Until you have actually collected data, this appendix will only contain the column labels in the first row, identifying the variables that you will record when you collect data later.  You may want to use an Excel spreadsheet as your data summary sheet. (required)
    4. Coding Guide - a description of the data file you will create on the computer from the data summary sheet.  The coding guide should tell you what columns of the data file contain codes for which variables, how many digits are allotted for the code for each variable, what the allowable values are for each variable, and what the levels of each variable represent (0=no and 1=yes, for example). (required)
    5. Data File - a computer file containing your data that you will use for analysis in SPSS.  The coding guide should describe exactly what the numbers in this file represent and how you got them from the data summary sheet.  Your data file might be identical to your data summary sheet, depending on how you constructed the data summary sheet.  Either way, your Coding Guide must clearly explain what the numbers in the data file mean.  (Not required until the final paper)

 

Some things to keep in mind and questions to consider: (You do not have to answer these point by point in your proposal, but these are issues that you should address and consider in order to do well on the project.)

  1. How will you insure that your coders are working independently and not influencing (biasing) one another during the initial coding of the data?
  2. If your coders disagree, how will you resolve the disagreements?
  3. How will you decide which ads to include and which to exclude?  How will you record how many ads were excluded, and how will you report this in your Results section when you write the final paper?
  4. Could someone else read your content analysis instructions for coding the ads (content analysis protocol) and code them the same way you did?  They should be able to.
  5. How many questions are you asking (how many hypotheses are you testing)?  It is ok to test only one.  If you choose to test more than one, keep the number to a minimum (no more than 2 or 3).
  6. How many DVs do you have?  It is possible to have more than one for testing a single hypothesis.  For example, if you were testing the hypothesis that women are more interested in partners with large feet compared to men (not an appropriate hypothesis for this assignment by the way), you might have the following 2 DVs:  "number of times feet mentioned in ad" (0 = no, 1 = once, 2 = twice, etc) and "expresses preference for large feet in partner" (0 = no, 1 = yes).  On the other hand, you might decide to use only one of these as a DV, or some other DV to measure the same thing. 
  7. What is the best way to scale the DV?  The "expresses preference for large feet" variable above is categorical (measured on a nominal scale) with two possible values. You might decide that adding a third category (2 = expresses preference for small feet) would be useful.  You might also decide that an interval scale would be more useful for this variable, and have your raters code how strong a preference the ad expresses for feet size (-7 = strong preference for small feet, 0 = no preference expressed, 7 = strong preference for large feet).  The advantage of using an interval scale like this is that you would have more information in your data about the feet size preferences.  The disadvantage is that the more detailed rating will be more subjective, and it will be harder to get two raters to agree, thus making your measure less reliable.  There are no hard and fast rules - you must think about whatever issues come up and use what you know about experimental methods to solve the problem.
  8. What values can your variables take?  How will you code things that do not fit into one of your expected categories or values?  Will you exclude them, have a code for "other," or alter your coding scheme (content analysis protocol)?  Again there are no simple rules about what to do.
  9. If you decide to change your content analysis protocol (coding scheme), how will you go back and re-code the data?  You will need to be able to retrieve and identify the ads you used, or the relevant information in the ads.  You should consider this question when deciding whether you will transcribe information from the ads to data sheets before creating the data summary sheet, or simply have coders put their ratings directly on the summary sheet while looking at the original articles.
  10. Think about the path from the observations (the data) to the analyses that will let you test your hypotheses, and make sure that you have a clear idea of how you will get from one end of this path to the other.  Here is an outline of the steps you will need:

 

Path from the data to the test of your hypothesis:

 

Ads (observational data)

â

Data Sheets (optional) 

â

Content Analysis Protocol (rules for assigning values to variables)

â

Data Summary Sheet (records the values of the variables)

â

Coding Guide (tells what the numbers in the data file mean and what the variables are)

â

data file for analysis on computer (may or may not be identical to the data summary sheet)

â

check for invalid data and outliers (and remove or correct them)

â

descriptive statistics (for the table presenting the means or proportions in the paper)

â

inferential statistics (to test the hypothesis)

 

 

A sample data summary sheet:

                                                Writer ----------------------------       seeking-----------------------

Paper   page     date         ad#   gender  age  quality1   quality2  gender   quality1   quality2

Trib      c48      10-9-00    1     male    34       big        small                 female       small        big

Trib      c48      10-9-00    2     female 24        big        big                    female       small        small

 

A sample coding guide: (for the first 7 columns in the above data summary sheet)

 

Column            digits    variable            values                                       notes

1                      1          paper               1=Chicago Tribune, 2=Chicago Sun Times                  

2                      3          page                 first digit = section (a=1,b=2, etc), last 2 digits = page number

3                      6          date                  mmddyy (month, day, year)

4                      3          ad number        any whole number

5                      1          gender              1=male, 2=female, 3=not specified

6                      3          age                                                      

7                      1          quality1            1=small, 2=big, 0=not specified

…etc.

 

(For column 7, what about "average"?  How would that be coded?)

 

Sample data file: (for the first 7 columns in the above data summary sheet)

1 348 100900 001 1 034 1 ….

1 348 100900 002 2 024 1 …..

Revised Research Proposal (due by date in syllabus)

 

The revised research proposal should contain the same parts as the original proposal with the following changes and additions:

 

  1. The Method section should be written in full, in APA format, rather than in outline form.  It should be very close to or identical to the Method section for the final paper.  Be sure that you have addressed all the comments you received on your original Method outline.
  2. Collect some pilot data from at least three or four ads.  Go through the full content analysis protocol for your study with three or four ads, and include that data in your revised data summary sheet. 
  3. Add another appendix labeled "Data File."  It should contain three or four lines (one for each ad in your pilot data sample) and be in the format that your Coding Guide specifies.  Include an appendix labeled “Data File” even if it is identical to your data summary sheet.  (See the instructions for the first draft of the research proposal if you are not sure what the Data File should be.)
  4. For the  Results section, provide an outline of the entire results section.  It should include a description of the data you will report (for example: "The mean shoe sizes for each handedness group are reported in Table 1," if your IV was handedness and your DV was shoe size - obviously, these are not variables that you would use in your study.)  It should also include a description of how you will identify outliers and what you will do with them, if you have any quantitative variables that might produce outliers.  Also, re-state your prediction (or predictions if you are testing more than one hypothesis in your study).  Finally, you must say what statistical test(s) you will use to test your hypothesis, and exactly how you will use it.  For example, if your hypothesis was that the older the person placing the ad was, the bigger their feet would be, you might say "We predicted that (or 'Our hypothesis was that') older advertisers would have larger feet than younger ad placers.  We will calculate the correlation coefficient between age of ad placer and his or her feet size to test this hypothesis.  A statistically significant positive correlation would confirm the prediction."  (Note:  You are more likely to use a t-test or a chi-square test than a correlation for your study)
  5. "References."  List (in correct APA format) at least 5 journal articles that you will cite in the introduction to your paper.  To find appropriate articles, you should do a literature search on the topic of mate selection in PsycInfo, and use the two references given in this handout as starting points for an SSCI search.  Try to keep your final references list to between 5 and 10 articles.  Title this list "References" and put it after the Discussion section (or after the Results section if you have not yet written the Discussion section) and before the appendices.
  6. Add a table that will present your findings (the table you referred to in your Results section outline).  Put all the appropriate labels and captions in the table and on its axes.  The means or proportions in your table should be calculated from your pilot data.  Put the table in the appropriate place, after the appendices.  The table can be typed manually once you know the means – you do not have to use SPSS to produce it.
  7. All other sections of the research proposal should also be revised in response to the comments you received.
  8. If you have already collected all of your data, you may choose to report all of it in this draft of the paper rather than just 3 or 4 cases.  If you do, you will get better feedback for writing your final draft and it will probably improve your score on the final paper as a result.
  9. Along with the revised proposal, turn in your original proposal that contains the instructor’s comments and suggestions.  Failure to include this will result in a significant penalty.

Final Paper

 

The final paper should be a manuscript in APA format presenting the findings of your study.  You are limited to 10 pages (not including references, appendices, tables, and figures).  Remember that clarity is the most important characteristic of good scientific writing, but brevity is desirable as well.  Ten pages is a maximum, not a minimum.  Say what you need to say - no more and no less. 

 

Your paper is required to contain at least the following sections:

 

 

Your introduction and discussion sections can be fairly brief.  The emphasis in this assignment will be on the method and results sections.  Your final paper should address any comments you received on the earlier drafts (research proposals). 

 

Late papers will be penalized 20% per day, and no papers will be accepted after the final exam.

 

The grading sheet for the final version of the paper is also attached so that you can see how your work will be evaluated.  Please attach it to the end of your final paper when you turn it in.

 

**You must also turn in both previous drafts (the Proposal and Revised Proposal) that have the instructor’s comments on them.  Paper-clip both of them to your final paper.  Failure to include these drafts will result in a significant penalty.
Grading sheet: Final Project             Name 1   _____________________________________

(Attach to end of FINAL paper)          

(Do NOT include with proposal / draft) Name 2   _____________________________________

  

                                                                        Grade:   _________________

 

Awarded     Possible*                                                          *Point values for specific content are approximate

_____  20        On time (including attaching the graded previous drafts)

_____  8          Format

_____  10        Clarity and style

_____  2          Abstract: summarizes hypothesis, methods, results

_____  8          Introduction

(5)        clear statement of hypothesis or hypotheses

(3)        cite published articles and motivate the hypothesis

_____  23        Method: should include the following information (subheadings optional)

(5)        Participants and Materials

(7)        Design: Independent and dependent variables clearly identified

(11)      Procedure: 

(2)        How the ads were selected.

(6)        How values were assigned to the DV (may also refer to Content Analysis Protocol in appendix)

(1)               How many raters/coders used to assign values for the ads

(2)        Other information as needed

_____  12        Results

(2)        state prediction

(4)        state results descriptively and refer the reader to a table or figure

(3)        correctly state the results of an inferential statistic. 

(3)        report inter-rater agreement rate  and how differences resolved.

_____  4          Discussion:

_____  4          References:

_____  2          Appendix: Data Summary Sheet. 

_____  2          Appendix: Coding Guide.   

_____  2          Appendix: Content Analysis Protocol.    (Content may also contribute to score for “Method”)

_____  3          Table or Figure:  presents the results as described in the results section.

 

Total Points:

__________