introduction - web viewthis is the fourth lab report of human factor ie342. this report is about the...

Cover Page

Table of ContentsIntroduction....................................................................................................................1

Objectives.......................................................................................................................1

Procedure........................................................................................................................1

Equipment......................................................................................................................3

Results............................................................................................................................4

Calculations....................................................................................................................5

Conclusion....................................................................................................................11

References....................................................................................................................12

Introduction This is the fourth lab report of human factor IE342. This report is about the Anthropometric Measurements of human body as one of related subject to human factor as well as vision and audition experiments on previous reports. Anthropometry is the measurement of people and the analyses of those measurements for various purposes like increasing capability of worker and makes the workplace more comfortable [1]. These measurements include all physical dimensions of the human body like: weight, height, waist,…etc. anthropometry plays an important role in industrial design, clothing design, ergonomics and architecture where statistical data about the distribution of body dimensions in the population are used to optimize product. Next sections will present the objectives and the procedure of this experiment, and discuss the results.

Objectives The main objective of this experiment is:

1- Understanding the uses of Anthropometric Measurements and its importance in industry.

2- Understanding the correct method to collect the data of Anthropometric Measurements, and be familiar with tools that are using to measure.

3- Understanding the way to analyze the data and comparing the results to the average results of human been in different area.

Procedure The studied variables included 36 anthropometric parameters as well as some basic parameters including: age, ethnic origin, father’s occupation and family size; the latter two parameters may be used as indicators of the socioeconomic status, ethnic origin is an indicator for heredity. The studied parameters are showing in figure (1). The procedures of this lab. Exercise can be summarized in the following points:

1- Students are divided into groups. Each group consists of two students. 2- Each student of the two should take the 36 anthropometric measures of the

other one and record them in the attached data collection form. 3- The collected 36 anthropometric measures are assigned to the students so that

each student will take one of the 36 anthropometric measures of the class to analyze it.

4- The analysis includes: a) Testing the normality of each anthropometric measure. b) Calculating the 5th, 50th and 95th percentile.

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Equipment The instruments used in this lab exercise include the following:

1. Metric Scale, which is of the physician’s type. It has a movable rod in the range of 75 cm to 195 cm with an incremental scale of 1 cm. It is used to

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Figure 1 Anthropometric Measurements

measure the stature; the eye standing, the shoulder standing, and elbow standing height. The metric scale is also equipped with a weighing balance of up to 160 kg capacity an incremental unit of 100 gram (0.1 kg). The weight measurements are recorded to the nearest 0.5 kg. The Metric Scale is shown in figure (2).

2. Chest Depth Caliber, which is of the physician’s type. It has a movable rod in the range of 1cm to 60 cm with an incremental scale of 1cm. It is used to measure the chest depth, chest breadth, waist depth, waist breadth, head length, head breadth and neck breadth. The Chest Depth Caliber is shown in figure (3).

3. Breadth Scale, which is of the physician’s type. It has a movable rod in the range of 1 to 100 cm with an incremental scale of 1 cm. It is used to measure the shoulder breadth, hip breadth, upper limb breadth, forward grip reach, elbow fingertip length, shoulder elbow length, thigh thickness, buttock-knee length, foot length, foot breadth, hand length and hand breadth. The Breadth Scale is shown in figure (4).

4. Fat Caliper (Skin Fold Caliper), which is adjustable from 1 to 60 mm with increment of 1 mm. It is used to measure fatness. The Fat Caliper is shown in figure (5).

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Figure 3the Metric Scale Figure 2 Chest depth Caliper

ResultsThis experiment measures different anthropometric parameters for all the group’s students, shown in table 1.

Table 1 Sample Data of Group's students

No. Variables Name Student #1

Student #2

Student #3

3 Age 22 214 Ethnic Origin Arab Asian5 Father’s Occupation Manager Teacher6 Family Size 8 97 Weight 52 58 70.58 Height 152 157 1709 Eye Height Standing 142 146 157.510 Shoulder Height standing 128 128 14111 Elbow Height Standing 94 96 106.512 Waist Height Standing 98 93 10813 Standing Vertical Grip Reach 182 186 20914 Height Setting 77 77 87

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Figure 4 Skinfold caliper Figure 5 flexible tape measures

Figure 6 Shoulder caliper

15 Eye Height Sitting 68 65 7416 Shoulder Height Sitting 51 49 5417 Elbow Height Sitting 15 18 2118 Sitting Vertical Grip Reach 103 113 11919 Over knee Height From Floor 51 51 5520 Under knee Height From Floor 43 42 4721 Chest Depth 20 24 25.522 Chest Breadth 22 36 26.523 Waist Depth 18 22 2624 Waist Breadth 25 32 3025 Head Length 18 19 18.526 Head Breadth 15 21 1527 Neck Breadth 8 9 1028 Shoulder Breadth 38.2 44 3829 Hip Breadth 36 35 3830 Upper Limb Length 70 65.5 76.5

31 Forward Grip Reach 69 67 7532 Elbow Finger Tip Length 42 40 3933 Shoulder Elbow Length 37.2 32 3734 Tight Thickness 15 16 1835 Buttock Knee Length 51 55 5636 Buttock to Hollow of Knee

Length43 49 48

37 Foot Length 21 22 2438 Foot Breadth 7.6 9 9.539 Hand Length 18 17 1840 Hand Breadth 8.5 9 1041 Fat Thickness 30 20 2742 Chest circumference 81 88 9843 Waist circumference 68.7 77 90.5

CalculationsIn this experiment, each student in each group will take one variable to measure and compare the sample result with population’s result. Population data is shown in table 2.

Table 2 The Population data of the variables that will be measure

Variables:No. 17: Elbow height

setting18: sitting vertical grip reach

19: Over knee Height From Floor

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1 22.5 116 502 21.5 117 49.53 18 113 514 15 103 515 21 113 506 16 115 487 23 114 508 21 116 509 20 103 5410 26 117 5511 20 109 5212 23 111 5113 22 102.5 5214 20 110 5015 20 107 5116 24 112 5217 25.5 119 5418 32 123 5619 30.5 114.5 4420 32 139 5821 23 114 5422 25 121 5523 20 107 5124 21 119 5525 16 115 5626 29 102 5027 22 102 5128 20 111 5229 31 123 5330 23 163 5231 29 120 5132 20 109 5233 20 107 5134 22 102 51

Table 3 The Categories that each student will compare with

Variable Student #1 Student #2 Student #317- Elbow height setting Category = 15

18 - Sitting Vertical Grip Reach

Category =113

19 - Over knee Height From Floor

Category = 55

Student #1 Student number 1 will takes variable number 17 which is Elbow height setting and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.

First: The hypothesis is:

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H0: The Population data are normally distributed for variable no. 17H1: The Population data are not normally distributed for variable no. 17

Second: Entering the population data in Minitab and perform the Chi-Square goodness of fit test.

Third: The result is:

Calculating result: Chi-Square = 26, P-Value = 0.054Tabulated result: Chi-Square = 26.296, α = 0.05

Concluding result: Since, Chi-Square = 26 < 26.296 and, P-Value = 0.054 > α = 0.05, Do not reject H0 and conclude that the data is normally distributed for variable 17 which is the Elbow height sitting.

Comparison: Student #1 has a Category = 15 which has a value = 1.Since 1 is near the expected value = 2 that is shown in figure 7, then, the category that student #1 has, does not cause significant difference.

Calculation of the Percentiles:

For the normal distribution the any percentile can be calculated

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Figure 7 The Expected and Observed values of the population of Variable 17

using the following formula:

Xp = X + Zp * S where

Xp is the percentile value

X is the average value of the sample data

Zp is the value of Z from the standard normal distribution table that corresponding to

the desired percentile

S is the standard deviation value of the sample data

The Z values of the standard normal distribution corresponding to the commonly used percentiles are shown on table 4 below:

Table 4 The Z values

Percentile P Zp

1st 0.01 -2.332.5th 0.025 -1.965th 0.05 -1.6410th 0.1 -1.28

17th 0.17 -0.955

50th 0.5 0.0083rd 0.83 0.95590th 0.9 1.2895th 0.95 1.64

97.5th 0.975 1.96

99th 0.99 2.33

The 5th percentile can be calculated as follows:

X0.05 = X + Z0.05 * SX0.05 = 16 cm

The 50th percentile= X0.5 = 22 cm

The 95th percentile=X0.95 = 31.35 cm

We can conclude that 95% from the population has elbow height while setting of 16cm, 50% has 22cm and 5% has 31.35cm.

Student #2

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Student number 2 will takes variable number 18 which is sitting vertical grip reach and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.

First: The hypothesis is:H0: The Population data are normally distributed for variable no. 18H1: The Population data are not normally distributed for variable no. 18



Calculating result: Chi-Square = 4.82353, P-Value = 1.00Tabulated result: Chi-Square = 30.144, α = 0.05

Concluding result: Since, Chi-Square = 4.82353 < 30.144 and, P-Value = 1 > α = 0.05, Do not reject H0 and conclude that the data is normally distributed for variable 18 which is sitting vertical grip reach.

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Comparison: Student #2 has a Category = 113 which has a value = 2.Since 2 is near the expected value = 1.7 that is shown in figure 8, then, the category that student #2 has, does not cause significant difference.



X0.05 = X + Z0.05 * SX0.05 = 102 cm

The 50th percentile= X0.5 = 113.5 cm

The 95th percentile= X0.95 = 128.6 cm

We can conclude that 95% from the population has elbow height while setting of 102cm, 50% has 113.5cm and 5% has 128.6cm.

Student #3 Student number 3 will takes variable number 19 which is over knee Height from Floor and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.

First: The hypothesis is:H0: The Population data are normally distributed for variable no. 19H1: The Population data are not normally distributed for variable no. 19



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Calculating result: Chi-Square = 24.2353, P-Value = 0.007Tabulated result: Chi-Square = 18.307, α = 0.05

Concluding result: Since, Chi-Square = 24.2353 >18.307and, P-Value = 0.007 < α = 0.05, Reject H0 and conclude that the data is not normally distributed for variable 19 which is knee Height from Floor.

Comparison: Student #3 has a Category = 55 which has a value = 3.Since 3 is near the expected value = 3.09091 that is shown in figure 9, then the category that student #3 has, does not cause significant difference.



X0.05 = X + Z0.05 * SX0.05 = 48.975 cm



We can conclude that 95% from the population has elbow height while setting of 48.975cm, 50% has 51cm and 5% has 56cm.

Conclusion

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References[1] "umtri," [Online]. Available:

http://mreed.umtri.umich.edu/mreed/research_anthro.html. [Accessed 27 2 2016].

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