Post on 23-Jan-2018
CLIQUES AND DIVERSITY In Various Institutions
Max Korten
SOAR 2015
Dr. Debra Wetcher-Hendricks
DO They continue on into higher education???
According to Johnson (2011)…-college size may play an important role in Considered together, these ideas relationships among students. suggest an association between
−students at small liberal arts schools large schools and cliques. My in-meet different types of people than dependent observations seem to students at large schools do. support the idea that cliques are
relatively uncommon at small. According to Benediktsson (2012) , diverse schools. However, I believe more experiences and acquaintances imply the formal analysis is necessary to existence of cliques. provide evidence
• H1: There is a positive correlation, between the size of an institution and the level of student involvement in cliques. (rsc>0)
• H2: There is a negative correlation, between the size of an institution and the the level of student involvement in cliques. (rsc<0)
• Ho: There is no relationship between the size of an institution and the level of student involvement in cliques. (rsc=0)
The following null hypotheses may be investigated based upon trends noticed in the data collected.
• Males and females have equal mean levels of involvement in cliques. (Ho: μM=μF)
• “Greeks” and “non-Greeks” have equalmean levels of involvement in cliques. (Ho: μG=μNG)
• There is no relationship between the number of campus activities in which students are involved and their levels of involvement in cliques. (Ho: rAC=0)
What does the survey address?Among other things……• how many undergraduates at school
• current status (year) at college
• demographic categories
• close group of friends containing ONLY females or males
• organizations to which the students belongs
• whether the student “hangs out” with those from organizations to which he or she belongs
• whether the student feels pressure to “go along” with close group of friends’ thoughts and behaviors
• submitting IRB proposals to each school• contacting professors from each school upon IRB approval
(cluster sampling)Colleges contacted: Moravian, Cedar Crest and Muhlenberg College, along with local ones in Pennsylvania
visiting schools to hand out surveys to the students in classes for which professors gave approval. • Also used survey monkey as another method for research• providing Wawa gift cards to raffle winners among those
who take the survey
DATA ANALYSIS PLANS• SPSS
• correlation and regression analysis to test original hypothesis; ANOVA possible as well to compare group means.
• Possible investigation of differences in level of involvement in cliques - at comparatively large and comparatively small
schools (t-test)-within categories identified in potential (secondary)
hypotheses (t-test)-within other subcategories of students that emerge as potentially relevant (t-test or ANOVA)
-as related to involvement in campus activities (correlation and regression analysis)
All statistics use only subjects who reported institution size with > 1,000. There were only two subjects in the first category (schools with under 1,000) , and responses are not representative of the population.
Statistics
What is your age?
N Valid 87
Missing 30
What is your age?
Frequency Percent Valid Percent
Cumulative
Percent
Valid 19 10 8.5 11.5 11.5
20 14 12.0 16.1 27.6
21 13 11.1 14.9 42.5
22 19 16.2 21.8 64.4
23 1 .9 1.1 65.5
99 30 25.6 34.5 100.0
Total 87 74.4 100.0
Missing System 30 25.6
Total 117 100.0
More Data analysis
The “mean” represents the clique score among college students. The “N” represents the number of students who took the whole survey from that institution size. Very high for the big schools, and low among the smaller institutions.
Descriptives
score
N Mean Std. Deviation Std. Error
95% Confidence Interval for
Mean
Minimum Maximum Lower Bound Upper Bound
1,000 - 4,999 23 16.39 2.726 .568 15.21 17.57 11 20
5,000 - 9.999 8 17.38 1.768 .625 15.90 18.85 16 20
10,000 - 14,999 5 16.60 2.608 1.166 13.36 19.84 13 20
15,000 - 19,999 14 17.21 2.486 .664 15.78 18.65 13 21
20,000 or more 15 17.87 1.995 .515 16.76 18.97 15 21
Total 65 17.05 2.407 .299 16.45 17.64 11 21
ANOVA
score
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 22.218 4 5.554 .956 .438
Within
Groups 348.644 60 5.811
Total 370.862 64
Anova and ind. Sample test
Group Statistics
?How many
undergraduates
attend your
college or
university N Mean Std. Deviation
Std. Error
Mean
score >= 6 15 17.87 1.995 .515
< 6 50 16.80 2.483 .351
Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower Upper
score Equal variances
assumed .603 .440 1.521 63 .133 1.067 .702 -.335 2.469
Equal variances
not assumed 1.711 28.282 .098 1.067 .623 -.210 2.343
Group Statistics
?How many
undergraduates
attend your
college or
university N Mean Std. Deviation
Std. Error
Mean
score 1,000 - 4,999 23 16.39 2.726 .568
20,000 or more 15 17.87 1.995 .515
Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower Upper
score Equal variances
assumed 1.733 .196 -1.802 36 .080 -1.475 .819 -3.136 .186
Equal variances
not assumed -1.923 35.425 .063 -1.475 .767 -3.032 .081
Group Statistics
?How many
undergraduates
attend your
college or
university N Mean Std. Deviation
Std. Error
Mean
score >= 3 42 17.40 2.165 .334
< 3 23 16.39 2.726 .568
Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower Upper
score Equal variances
assumed 1.523 .222 1.644 63 .105 1.013 .616 -.218 2.245
Equal variances
not assumed 1.537 37.423 .133 1.013 .659 -.322 2.349
So what does this all mean?!
• Based upon these results, this indicates that there is a mild, but somewhat inconsistent trend for clique involvement to increase with institution size. The pattern is not greatly evident when noticing small differences in institution size, but is useful when comparing small and big colleges.
SOURCES(not for the whole project…just for this presentation)
Benediktsson, M.O. (2012). Bridging and Bonding in the
Academic Melting Pot: Cultural Resources and Network
Diversity. Sociological Forum 27.1, 46-69. Web. 26
June 2015.
Johnson, C.Y. (2011, May 8). Collaboration: the mother of
invention. The Boston Globe. Retrieved from http://articles.
boston.com/2011-05-08/news/29523118_1_research-
scientist-journals-selkoe.