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

VI. Bibliography

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Cooks Distance. MathWorks. Retrieved March 28, 2015 from http://www.mathworks.com/help/ stats/cooks-distance.html

DFFITS. STATISTICA Help. Retrieved March 28, 2015 from http://documentation.statsoft.com/ STATISTICAHelp.aspx?path=glossary/GlossaryTwo/D/DFFITS

Melamed, T. (1992). Personality Correlates of Physical Height. Personality and Individual Differences. Retrieved March 29, 2015, from http://www.google.com/m?hl=en&source=a ndroid-browser-type&q=Why+Do+Women+All+Seem+to+Want+Taller+Men%3F++eHar mony+Advice)

Nettle, D. (2002). Womens height, reproductive success and the evolution of sexual dimorphism in modern humans. The Royal Society , 1919-1923.

Parmer, T. (1998). Characteristics of Preferred Partners: Variations Between African American Men and Women. Journal of College Student Development , 461.

Pawlowski, B., Dunbar, R.I.M., & Lipowicz, A. 2000. Tall Men Have More Reproductive Success. Nature. Retrieved March 28, 2015 from http://www.google.com/m?hl=en&source=android-browser-type&q=Why+Do+Women+All+Seem+to+Want+Taller+Men%3F+-+eHarmony+Ad vice)

Prigg, M. (2014, February 10). Daily Mail UK. Retrieved March 30, 2015, from www.dailymail.co.uk: http://www.dailymail.co.uk/sciencetech/article-2556117/Height-really-does-matter-relationship-women-say-scientists.html

PROPHET StatGuide: Do your data violate paired t test assumptions? Retrieved March 28, 2015 from http://www.basic.northwestern.edu/statguidefiles/ttest_paired_ass_viol.html

Sear, R. (2010). Height and Reproductive Success: Is BiggerAlways Better? The Frontiers Collection , pp. 127-143.

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