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.