Guys Height and His Chances of Getting into RelationshipsJohnrel
Sucalit, Charidel Etulle, Princess Moya, Gay Bricanyl CalderonI.
IntroductionMelamed (1992) said that taller men are seen to be more
dominant and fierce. A larger man has the capability to provide
their offspring more protection and better qualities to be passed
for the next generation, thus giving them a greater social status.
Height has been an indicator for viewing a man to be large.
(Pawlowski, Dunbar, &Lipowicz, 2000). According to Stulp,
Buunk, & Pollet (2013) in their study entitled Women Want
Taller Men than Men Want Shorter Women one of the preferences of
humans for their mate is a person's physical characteristics such
as the height. In the same study, it showed that a person's
satisfaction with own height and his/her partner's height seemed to
be related to this preference.
Different studies were made such as one conducted by Dr.
Boguslaw Pawlowski entitled Conditional Male Preferences, and one
conducted by George Yancey entitled Does Height Matter? An
Examination of Height Preferences in Romantic Coupling revealed why
women want taller men. Both studies used American respondents.
Articles were written in the Philippines about the same topic but
all were basing on results of American Studies.
With this, the researchers would also want to find out if there
is a significant correlation between the height of males in Cebu
Normal University and the number relationships he have had. And
that if the height of a guy affects his chances of getting into
relationships.
II. Review of Related LiteratureStudies were already conducted
in relating physical attributes to the success of romantic
relationships of individuals all across the globe. Palmer (1998) in
a study examining the interaction of gender and education as a
factor on mate selection showed that height is one of the
significant factors on selecting a mate.
However, a paper by Nettle (2002) regarding mens height and
relationship success showed that height was weakly but a
significant factor for this matter. Although there are published
papers that conduct studies regarding the connection between height
of both men and women and productivity and mating choices, still
there are no researches yet regarding the correlation of mens
height and romantic relationships alone were made. Moreover, a
research about the benefits of height during adulthoodmortality
rates, mating success, and fertility outcomes shows that although
height plays a big deal in general public; still it is rarely
advantageous to men but not universally beneficial for women (Sear,
2010).As to why women prefer taller men is not news anymore. Yancey
and Emerson (2014) in their paper where 455 males and 470 females
throughout US were the respondents, found out that 13. 5 percent of
men wanted to date only women shorter than they were and 48.9
percent of women wanted to date only men who are taller than they
are (Christian, 2014; Prigg, 2014). The same study also concluded
that femininity and protection were the main reasons why women
prefer tall partners (Christian, 2014). Yancey, the studys lead
author believes that traditional societal expectations and gender
stereotypes are the main reasons that explain why men and women
have height preferences (Prigg, 2014).III. MethodologyThe
researchers have gathered their data in Cebu Normal University. The
researchers agreed to ask guys of age 19 only as to have the age
factor controlled. They measured the heights of 43 19-year old guys
and also asked the total number of relationships they have had. The
researchers will use Correlation and Regression to determine if
there is a relationship between the height of a guy and the number
of his relationships. The researchers will remove extreme outliers
and very influential data by conducting DFFITS, Cooks Distance and
T-test. Cook's distance is useful in identifying outliers in
theXvalues. It can also show the influence of each observation on
the fitted response values
(http://www.mathworks.com/help/stats/cooks-distance.html). DFFITS
is useful in testing for leverage and influence of a specific case
in regression linear models
(http://documentation.statsoft.com/STATISTICAHelp.aspx?path=glossary/GlossaryTwo/D/DFFITS).
T-test is useful in determining the presence of outliers in the
sample population
(http://www.basic.northwestern.edu/statguidefiles/ttest_paired_ass_viol.html).
After all outliers have been removed, the researchers plot the data
in a scatter plot and solved the coefficient of correlation, r, to
find out if there is really a correlation with the height and
number of relationships of the guys. If the absolute value of the
computed value of r exceeds the critical value, the researchers can
conclude that there is a linear correlation. Otherwise, there is no
sufficient evidence to support the conclusion of a linear
correlation. The researchers made all graphs, tables and
calculations in this research in Microsoft Excel 2013.
IV. ResultsData Summary All 43 data were tested if any are
outliers. Data who has a significant t-test (< .05) nor a high
Cooks distance (> 1) or DFFITS (> 1) are the once who are
potential outliers, and so we remove and disinclude them in the
analysis. From the table, all the data who are marked with yellow
are the ones who have t-test (1) or a DFFITS value (>1) and must
be removed. There are 3 potential outliers removed therefore we
only have 40 data to consider in the analysis. n=40.
ObservationXY Pred YResidualLeverageMOD MSER-StudentT-testCook's
DDFFITS
116634.231315-1.231310.02432421.27406-0.270270.7883120.000931568-0.04267
215924.547234-2.547230.05694121.1409-0.570480.5714680.009989343-0.14018
317124.005658-2.005660.05827221.20612-0.448810.6559310.006355904-0.11164
4164154.32157710.678420.02410218.391792.5205370.0157040.0693926350.396113
516754.1861830.8138170.02729721.295890.1788090.8589690.0004594780.029954
615834.592365-1.592360.06923421.2448-0.358090.7221110.004872717-0.09766
716844.141052-0.141050.03217921.31239-0.031060.9753741.64357E-05-0.00566
816744.186183-0.186180.02729721.31202-0.040890.967582.40487E-05-0.00685
916324.366708-2.366710.02685421.16901-0.521440.6048650.003819322-0.08662
1015724.637496-2.63750.08343421.12317-0.599420.5521920.016613115-0.18085
1116124.456971-2.456970.03808121.15602-0.544650.5889480.005974225-0.10837
1216624.231315-2.231310.02432421.18534-0.490780.6261960.003059131-0.07749
1317503.825133-3.825130.11977920.89734-0.891880.3776630.054392675-0.329
1416324.366708-2.366710.02685421.16901-0.521440.6048650.003819322-0.08662
1517014.050789-3.050790.04766621.06858-0.681080.4996480.011762754-0.15237
16157.504.614931-4.614930.07609520.73662-1.054340.2978990.04565463-0.30259
1717503.825133-3.825130.11977920.89734-0.891880.3776630.054392675-0.329
1815714.637496-3.63750.08343420.95201-0.830060.4113140.031598938-0.25044
1917233.960527-0.960530.07078721.28809-0.215970.8300860.001818825-0.05961
2016104.456971-4.456970.03808120.79663-0.996490.3248560.019658987-0.19827
21159.534.524668-1.524670.0515121.25164-0.33960.7358940.003200606-0.07914
2216054.5021020.4978980.04655721.306410.1104680.9125770.0003052990.024411
2317783.734874.265130.16198120.770221.0223150.3126260.1008957220.449459
2416874.1410522.8589480.03217921.101780.6326290.5304880.0067521670.115355
2516324.366708-2.366710.02685421.16901-0.521440.6048650.003819322-0.08662
2617114.005658-3.005660.05827221.07308-0.67470.5036510.0142739-0.16783
2716344.366708-0.366710.02685421.30945-0.080530.9362099.16935E-05-0.01338
2816874.1410522.8589480.03217921.101780.6326290.5304880.0067521670.115355
2916504.276446-4.276450.02325920.84482-0.947750.3488090.010721365-0.14625
30163204.36670815.633290.02685415.034314.0871410.0001980.1666470370.67894
3116954.0959210.9040790.03896821.291650.1998630.8425750.0008292820.040246
3216154.4569710.5430290.03808121.305240.1199530.9051060.0002918280.023867
33164184.32157713.678420.02410216.519913.406670.0014840.1138600060.535373
34164.524.299012-2.299010.02344221.1776-0.505540.6158880.003124164-0.07833
3516724.186183-2.186180.02729721.19007-0.481540.6326950.003315769-0.08067
3616054.5021020.4978980.04655721.306410.1104680.9125770.0003052990.024411
37158.574.5697992.4302010.06284921.155360.5457920.5881670.0101627880.141342
38169.504.073355-4.073360.04307920.87943-0.911290.3674720.018770147-0.19335
3916784.1861833.8138170.02729720.939070.8450670.4029780.0100909220.141567
4016674.2313152.7686850.02432421.116490.6099720.5452460.004710030.096311
41163104.3667085.6332920.02685420.497671.2613070.2143280.0216382030.209524
4216244.41184-0.411840.03151321.30853-0.090660.9282060.000137029-0.01635
4316614.231315-3.231310.02432421.04537-0.71310.4798250.006415566-0.11259
Table 1. Calculations for OutliersX = height of menY = number of
relationships =Outliers.Figure 1.This shows the calculated
confidence interval for slope, confidence interval for intercept,
coefficient of correlation, coefficient of determination, etc.
These values were calculated in Microsoft Excel 2013 which will be
used in the further analysis of the data.
Figure 2. Scatterplot on Guys Height and their Number of
RelationshipsThe plot shows that the points are too scattered away
from the regression line. The equation of the line is y=0.0097x +
1.6776 and the coefficient of correlation is r =.0192 as calculated
in Figure 1. Hypothesis Testing Null HypothesisHo= p = 0(There is
no significant correlation between the heights of the guys and the
number of their relationships)Alternative HypothesisHi= p 0(There
is a significant correlation between the heights of the guys and
the number of their relationships)Method 1: Test statistics
t = .1233
The researchers found the critical value to be 2.024 by looking
on the table (See appendix 1) with degrees of freedom n 2 and
significance level of .05. The value of the calculated t value,
.1233 does not exceed or fall in the critical value 2.024.
Therefore we fail to reject the null hypothesis, p=0 and that there
is no sufficient evidence to warrant the claim that there is a
significant correlation between the height of a men and the number
of their relationships.
Method 2: Test Statistic is rr = .0192
Researchers found the critical value to be .312 by looking on
the table (See appendix 2) using n and not df (degrees of freedom)
which is equal to 40 with significance level of .05.The absolute
value of the r, .02 does not exceed or fall in the critical value
.312 which means we fail to reject the null hypothesis, p=0 and
that there is no sufficient evidence to warrant the claim that
there is a significant correlation between the height of men and
the number of their relationships.
Method 3: P- ValueFrom the calculation in Excel as shown in
Figure 1 in the ANOVA table, researchers found out that the P-
Value of the sample data is .906235197. Pvalue = 1 - .901600489
P-value = (.093765) X 2(right tailed)P- Value = .18753
From the calculations we get the p-value which is equal to
.18753. Since the test is a two-tailed test the significance level
of both tails are .025. Comparing the p-value with the significance
level, we see that the p-value is greater and doesnt exceed or fall
in the significance level. Therefore we fail to reject the null
hypothesis, p=0 and that there is no sufficient evidence to warrant
the claim that there is a significant correlation between the
height of a guy and his number of relationships.V. Discussion,
Conclusion and Recommendation
Discussion:The plot shows that the points are too scattered away
from the regression line with a small coefficient of correlation,
r= 0.0192. Based on the results from the different methods
conducted, it showed that there is no sufficient evidence to
warrant the claim that there is a correlation between the height of
a guy to the number of relationships hes involved in. Therefore we
cannot say that a mans height directly affects the possible number
of relationships he can have or if it affects, maybe just very
small as implied by the value of r which is not significantly
big.The results of this research doesnt strongly support Palmers
research on 1998 that states that height is a significant factor in
selecting a mate. Moreover, the results of the research coincides
with Nettles research in 2002 study regarding mens height and
relationship success, it showed that height was weakly but a
significant factor which also reflected in the test results that
height is a weak factor in determining the number of relationship a
man can have.
In Yancey and Emersons research in 2014, they said that almost
50% of women prefer to date taller men. This percentage of women
strongly says that height is a big factor in womens preference on
men. However the result of their papers is not reflected on the
results of this research.Conclusion:Height alone, is a weak factor
for mens possibility of having more number of relationships. A guys
height doesnt really say much about his chances of getting into a
relationship. Tall guys dont have significantly higher number of
relationship compared to short guys.
There might be more influential factors that can affect a guys
chance of getting into relationship such as weight, educational
background, financial status, behavior, etc.
Recommendations:Based on the results, the researchers recommend
the following:1. Conduct also research to girls that will prove
that they prefer taller than shorter men2. Have more respondents.3.
Try to have extremely tall guys and extremely short guys to have a
bigger range in mens height.4. Researchers could also make research
on the other factors that can affect the chances of a guy to get
into a relationship such as weight, educational background,
financial status, etc.
AppendixAppendix 1t Distribution: Critical t Values
Appendix 2Table of critical values for Pearson correlation N
(notdf) is in column 1One Tailed Probabilities
0.050.0250.0050.0005
Two-Tailed Probabilities
N0.10.050.010.001
40.9000.9500.9900.999
50.8050.8780.9590.991
60.7290.8110.9170.974
70.6690.7540.8750.951
80.6210.7070.8340.925
90.5820.6660.7980.898
100.5490.6320.7650.872
110.5210.6020.7350.847
120.4970.5760.7080.823
130.4760.5530.6840.801
140.4580.5320.6610.780
150.4410.5140.6410.760
160.4260.4970.6230.742
170.4120.4820.6060.725
180.4000.4680.5900.708
190.3890.4560.5750.693
200.3780.4440.5610.679
210.3690.4330.5490.665
220.3600.4230.5370.652
230.3520.4130.5260.640
240.3440.4040.5150.629
250.3370.3960.5050.618
260.3300.3880.4960.607
270.3230.3810.4870.597
280.3170.3740.4790.588
290.3110.3670.4710.579
300.3060.3610.4630.570
350.2830.3340.4300.532
400.2640.3120.4030.501
450.2480.2940.3800.474
500.2350.2790.3610.451
600.2140.2540.3300.414
700.1980.2350.3060.385
800.1850.2200.2860.361
900.1740.2070.2700.341
1000.1650.1970.2560.324
2000.1170.1390.1820.231
3000.0950.1130.1490.189
4000.0820.0980.1290.164
5000.0740.0880.1150.147
10000.0520.0620.0810.104
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