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Grip and Arm Strength and Performance - Essay Example

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The paper “Grip and Arm Strength and Performance” supports the view that physical strength is positively associated with one’s performance on the job. This work examines whether a data set on hand supports the view that physical strength positively affect one’s performance on jobs…
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Grip and Arm Strength and Performance
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Grip and Arm Strength and PerformanceI. IntroductionThe studies of Sharp (1994), Blair et al. (20040, Kolley et al. (2012) and Freide (2012) support the view that physical strength is positively associated with one’s performance on the job. This reasonable to expect and this work examines whether a data set on hand supports the view that physical strength positively affect one’s performance on jobs that are physically demanding. For comparative purposes, the study also explored if physical strength positively affect one’s SIMS score. II. Problem Does the data set on hand support the view that physical strength enhances one’s performance in jobs that are physically demanding?

How do we compare the findings on the data set with the possible effect of physical strength on SIMS performance?III. Data, Computations and Analysis The data set involves a sample of 15 with data on grip and arm strength, performance ratings on physically demanding jobs and SIMS performance. Variable name “Grip” refers to grip strength, variable name “Arm” refer to arm strength, variable name “Rating” refer to ratings on a physically-demanding job while variable name “SIMS” refer to performance on SIMS. 1. Data and Descriptive StatisticsTable 1.

Descriptive Statistics ParameterGripArmRatingSIMSMean104.0378.1038.69-0.23Median99.5083.0037.300.27Maximum136.50109.5056.602.30Minimum82.0038.0025.40-3.88Range54.5071.5031.206.18S.D.16.2023.758.981.81Variance262.55564.1180.583.28 Table 1 reflects the descriptive statistics on variable names Grip, Arm, Rating and SIMS. They were computed using Excel’s Statistical Function commands. We can note that in the data, if we compare the variances relative to the mean values of the four variables, there is high variability among all four variables.

This is easy to confirm if we divide the S.D. or the standard deviation by their respective mean in all the four variables. In all four variables the ratio of the standard deviation relative to the mean in each variable is at least 2. 2. Scatter Plots In this section, we use the graphical function of Excel to construct four scattergrams: Grip versus SIMS score, Grip versus Rating, Arm Strength versus Rating, and Arm Strength versus SIMS. The scattergrams are shown in the following four figures.

Grip and SIMS Score (grip on horizontal Grip and Rating (grip on horizontal axis, SIMS on the vertical axis) axis, Rating on the vertical axis) Arm strength and Rating (Arm strength on Arms Strength and SIMS (Arm strength Horizontal axis, Rating on the vertical axis) on Horizontal axis, SMS on the vertical axis) The foregoing scattergram patterns indicate the Grip Strength and SIMS as well as Arm Strength and Rating are possibly correlated but the same does not appear to be true between Grip and Rating as well as between Arm Strength and SIMS.

In the next section, however, or in the discussion of correlation coefficient, what will be shown is that Grip Strength and SIMS as well as Arm Strength and SIMS are the pairs which are highly correlated. Based on the correlation coefficients that will be shown in the next section, the seemingly high visual correlation between Arm Strength and Rating as well as the seemingly low visual correlation between Arm Strength and SIMS appear to be illusions created by the scales used in the graphs. The vertical scale used for Rating in Arm Strength versus Rating is in units of ones while the vertical scale used for Arms Strength in Arms Strength versus SIMS is in units of tens. 3. Correlation Coefficient This work determined several correlation coefficients between two variables.

The correlation coefficient is conveniently determined using Excel’s “Correl function.” According to Excel’s Help Function, the correlation coefficient is computed by Excel using the following formula:. Using Excel’s “Correl function,” the following correlation coefficients were obtained:Variables CorrelatedCorrelation CoefficientGrip and SIMS0.635Grip and Rating0.107Arm and Rating-0.087Arm and SIMS0.843Grip and Arm0.469 Based on the correlation coefficients computed by Excel, Grip Strength and SIMS are highly correlated as well as Arm Strength and SIMS. 4. Regression Analysis Because the earlier section showed that Grip Strength and SIMS are highly correlated as well as Arm Strength and SIMS, it appears appropriate that regression functions are constructed using the fact.

Using Excel’s Linest function for computing for linear regression, we get the following regression data from Excel: SIMS = 0.07 Grip - 7.62 (0.02) (2.52) R2 = 0.40 F-Stat = 8.80 In contrast, for the regression of SIMS by Arm Strength, Excel’s Linest function reported that the regression is of the form: SIMS = 0.06 Arm - 5.

26 (0.01) (0.93) R2 = 0.71 F-Stat = 32.03 Based on regression literature, indicates the percentage of the dependent variable that is explained by the independent variable (Davies 2007). Thus, 40% of the variation in the SIMS is explained by the variation in Grip Strength and 71% of the variation in SIMS can also be explained by the variation in SIMS. They need not add up to 100% because the fit need not be perfect. IV. Conclusion Based on the foregoing scatterplots, correlation coefficients and regressions, we have good regressions indicating that Arm Strength and Grip Strength positively influence SIMS Score.

However, this is not the case between physical strength and rating on physically demanding job. ReferencesBlair, S., LaMonte, M. and Nichaman, M., 2004. The evolution of physical activity recommendations: How much is enough. Journal of Clinical Nutrition, 79 (5), 918S-920S. Davies, S., 2007. Interpreting regression output. Available from: http://www.simon-davies.org.uk/Interpreting_OLS_Output(cross-sectional).pdf [Accessed 4 April 2013]. Friede, K., 2012. Body composition and military performance.

Journal of Strength and Conditioning Research, 26 (7), S87-S100. Koley, S., Kumaar, S. and Shadagopan, S., 2012. Andropometric, physical strength, body composition and performance test profiles of inter-district level male cricketers of Punjab, India. Anthropologist, 14 (5), 445-451. Sharp, M., 1994. Physical fitness and occupational performance of women in the U.S. Army. Physical Fitness and Occupational Performance of Women, 4(2), 80-92.

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