Difference between revisions of "SOCR EduMaterials Activities BMI Modeling Activity"
(→Data Summary) |
m (→Summary) |
||
Line 7: | Line 7: | ||
==Summary== | ==Summary== | ||
− | This activity uses a simplified version of the [[SOCR_Data_BMI_Regression| BMI data sets found here]]. Four cases of data were excluded due to extremely high BMIs that hinted at a mistake in the entry process. 10 variables from the original dataset were left out in the dataset presented here, though the same process presented here may be used on them for additional practice. | + | This activity uses a simplified version of the [[SOCR_Data_BMI_Regression| BMI data sets found here]]. Four cases of data were excluded due to extremely high BMIs that hinted at a mistake in the entry process. 10 variables from the original dataset were left out in the dataset presented here, though the same process presented here may be used on them for additional practice. |
− | |||
==Data== | ==Data== |
Revision as of 17:16, 30 January 2013
Contents
SOCR Educational Materials - Activities - SOCR Body Mass Index (BMI) Activity and Applications of the Chi-Squared Test
Often times when solving a problem from intro-level textbooks, we are told to assume that a population follows a normal distribution. Other times, a graph of the data will allow us to assume some degree of normality. This allows the use of a number of statistical analyses later on.
Motivation and Goals
The following activity will demonstrate one of the ways to test for normality, using the Chi-Squared test for Goodness-of-Fit. The model to fit will be the normal model. We will run this test on a human characteristic often assumed to fit at least some kind of normal model: BMI.
Summary
This activity uses a simplified version of the BMI data sets found here. Four cases of data were excluded due to extremely high BMIs that hinted at a mistake in the entry process. 10 variables from the original dataset were left out in the dataset presented here, though the same process presented here may be used on them for additional practice.
Data
Data Description
- Number of cases: 248
- Variables
- Underwater Density – Density determined via a graduated-cylinder type test
- Body fat—Calculated body density and tissue-type proportions using Siri’s equation (see the full dataset page)
- Height
- Weight
- BMI—Body Mass Index, calculated as \( \frac{weight}{height^2} \).
Data Summary
Statistic | Underwater_Density_(\( \frac{g}{cm^3}\)) | Body_Fat | Height(m) | Weight_(kg) | BMI |
---|---|---|---|---|---|
Mean | 1.0562 | 18.854 | 1.787 | 80.547 | 25.18643319 |
SD | 0.0184 | 8.0663 | 0.0659 | 12.0076 | 3.146481308 |
Raw Dataset
Underwater_Density(g/cm3) | Body_Fat | Height(m) | Weight(kg) | BMI |
---|---|---|---|---|
1.0708 | 12.3 | 1.72085 | 69.96662 | 23.6268 |
1.0853 | 6.1 | 1.83515 | 78.58488 | 23.33436 |
1.0414 | 25.3 | 1.68275 | 69.85322 | 24.66876 |
1.0751 | 10.4 | 1.83515 | 83.80119 | 24.88325 |
1.034 | 28.7 | 1.80975 | 83.57439 | 25.51738 |
1.0502 | 20.9 | 1.89865 | 95.3678 | 26.45525 |
1.0549 | 19.2 | 1.77165 | 82.10022 | 26.15703 |
1.0704 | 12.4 | 1.8415 | 79.83226 | 23.54155 |
1.09 | 4.1 | 1.8796 | 86.63614 | 24.5227 |
1.0722 | 11.7 | 1.8669 | 89.92469 | 25.80102 |
1.083 | 7.1 | 1.8923 | 84.48158 | 23.59294 |
1.0812 | 7.8 | 1.9304 | 97.97595 | 26.29208 |
1.0513 | 20.8 | 1.7653 | 81.87342 | 26.27277 |
1.0505 | 21.2 | 1.80975 | 93.09983 | 28.42574 |
1.0484 | 22.1 | 1.7653 | 85.16197 | 27.32805 |
1.0512 | 20.9 | 1.6764 | 73.82216 | 26.26827 |
1.0333 | 29 | 1.8034 | 88.79071 | 27.3013 |
1.0468 | 22.9 | 1.8034 | 94.9142 | 29.18415 |
1.0622 | 16 | 1.72085 | 83.3476 | 28.14538 |
1.061 | 16.5 | 1.8669 | 96.04818 | 27.55796 |
1.0551 | 19.1 | 1.7272 | 81.19303 | 27.21658 |
1.064 | 15.2 | 1.77165 | 90.94527 | 28.97505 |
1.0631 | 15.6 | 1.73355 | 63.61633 | 21.16878 |
1.0584 | 17.7 | 1.778 | 67.47187 | 21.34319 |
1.0668 | 14 | 1.72085 | 68.60585 | 23.16728 |
1.0911 | 3.7 | 1.8161 | 72.23458 | 21.90109 |
1.0811 | 7.9 | 1.7145 | 59.6474 | 20.29161 |
1.0468 | 22.9 | 1.7145 | 67.13167 | 22.83771 |
1.091 | 3.7 | 1.64465 | 60.44118 | 22.34529 |
1.079 | 8.8 | 1.7526 | 72.91497 | 23.73838 |
1.0716 | 11.9 | 1.87325 | 82.55381 | 23.52587 |
1.0862 | 5.7 | 1.80975 | 72.68818 | 22.19354 |
1.0719 | 11.8 | 1.80975 | 76.20352 | 23.26686 |
1.0502 | 21.3 | 1.8034 | 99.10993 | 30.47425 |
1.0263 | 32.3 | 1.8669 | 112.1507 | 32.17806 |
1.0101 | 40.1 | 1.651 | 86.97634 | 31.90854 |
1.0438 | 24.2 | 1.778 | 91.73906 | 29.01956 |
1.0346 | 28.4 | 1.73355 | 89.2443 | 29.69667 |
1.0258 | 32.6 | 1.7018 | 92.07925 | 31.79397 |
1.0279 | 31.6 | 1.778 | 98.42954 | 31.13594 |
1.0269 | 32 | 1.8161 | 96.16158 | 29.15561 |
1.0814 | 7.7 | 1.7272 | 56.81244 | 19.044 |
1.067 | 13.9 | 1.86055 | 74.50255 | 21.52229 |
1.0742 | 10.8 | 1.7145 | 60.55458 | 20.60023 |
1.0665 | 5.6 | 1.80975 | 67.35847 | 20.56625 |
1.0678 | 13.6 | 1.7399 | 61.57516 | 20.34028 |
1.0903 | 4 | 1.69545 | 57.83303 | 20.11898 |
1.0756 | 10.2 | 1.83515 | 71.78099 | 21.31407 |
1.084 | 6.6 | 1.7526 | 63.16274 | 20.56342 |
1.0807 | 8 | 1.72085 | 62.25555 | 21.02287 |
1.0848 | 6.3 | 1.8669 | 69.28623 | 19.87947 |
1.0906 | 3.9 | 1.7145 | 61.80196 | 21.02458 |
1.0473 | 22.6 | 1.8288 | 89.81129 | 26.85335 |
1.0524 | 20.4 | 1.7272 | 82.32702 | 27.5967 |
1.0356 | 28 | 1.7653 | 91.28546 | 29.29305 |
1.028 | 31.5 | 1.79705 | 91.85245 | 28.44267 |
1.043 | 24.6 | 1.67005 | 81.53323 | 29.23316 |
1.0396 | 26.1 | 1.86055 | 97.97595 | 28.30328 |
1.0317 | 29.8 | 1.7399 | 81.07964 | 26.78325 |
1.0298 | 30.7 | 1.78435 | 87.65673 | 27.5312 |
1.0403 | 25.8 | 1.7018 | 80.73944 | 27.87845 |
1.0264 | 32.3 | 1.778 | 93.21323 | 29.48588 |
1.0313 | 30 | 1.7145 | 83.2342 | 28.31567 |
1.0499 | 21.5 | 1.79705 | 68.71924 | 21.27933 |
1.0673 | 13.8 | 1.8161 | 70.19342 | 21.28222 |
1.0847 | 6.3 | 1.75895 | 70.42022 | 22.76095 |
1.0693 | 12.9 | 1.8161 | 71.1006 | 21.55727 |
1.0439 | 24.3 | 1.8161 | 75.97672 | 23.03568 |
1.0788 | 8.8 | 1.74625 | 66.56468 | 21.82886 |
1.0796 | 8.5 | 1.87325 | 72.91497 | 20.77903 |
1.068 | 13.5 | 1.6256 | 56.69905 | 21.45598 |
1.072 | 11.8 | 1.67005 | 64.86371 | 23.25642 |
1.0666 | 18.5 | 1.7145 | 67.24507 | 22.87628 |
1.079 | 8.8 | 1.7653 | 73.70876 | 23.65277 |
1.0483 | 22.2 | 1.7399 | 80.62604 | 26.63341 |
1.0498 | 21.5 | 1.78435 | 73.14177 | 22.97235 |
1.056 | 18.8 | 1.75895 | 77.67769 | 25.10668 |
1.0283 | 31.4 | 1.72085 | 74.27575 | 25.08193 |
1.0382 | 26.8 | 1.70815 | 68.15225 | 23.3576 |
1.0568 | 18.4 | 1.84785 | 86.29595 | 25.27301 |
1.0377 | 27 | 1.778 | 77.4509 | 24.49982 |
1.0378 | 27 | 1.75895 | 76.20352 | 24.63021 |
1.0386 | 26.6 | 1.7145 | 75.74993 | 25.76958 |
1.0648 | 14.9 | 1.70815 | 71.5542 | 24.52354 |
1.0462 | 23.1 | 1.67005 | 72.57478 | 26.02117 |
1.08 | 8.3 | 1.8415 | 80.17245 | 23.64186 |
1.0666 | 14.1 | 1.8542 | 79.83226 | 23.22016 |
1.052 | 20.5 | 1.778 | 80.28585 | 25.3966 |
1.0573 | 18.2 | 1.7653 | 81.53323 | 26.16361 |
1.0795 | 8.5 | 1.7907 | 74.95614 | 23.37553 |
1.0424 | 24.9 | 1.82245 | 87.31653 | 26.28968 |
1.0785 | 9 | 1.8923 | 83.57439 | 23.33959 |
1.0991 | 17.4 | 1.97485 | 101.8315 | 26.11042 |
1.077 | 9.6 | 1.86055 | 85.61556 | 24.73261 |
1.073 | 11.3 | 1.6891 | 73.70876 | 25.83499 |
1.0582 | 17.8 | 1.73355 | 70.98721 | 23.62149 |
1.0484 | 22.2 | 1.8288 | 89.3577 | 26.71773 |
1.0506 | 21.2 | 1.8669 | 90.03809 | 25.83355 |
1.0524 | 20.4 | 1.8288 | 78.81167 | 23.56449 |
1.053 | 20.1 | 1.80975 | 78.35808 | 23.92471 |
1.048 | 22.3 | 1.87325 | 89.2443 | 25.4325 |
1.0412 | 25.4 | 1.75895 | 80.28585 | 25.94968 |
1.0578 | 18 | 1.7399 | 75.06954 | 24.79792 |
1.0547 | 19.3 | 1.8669 | 90.83187 | 26.0613 |
1.0569 | 18.3 | 1.88595 | 92.19265 | 25.92006 |
1.0593 | 17.3 | 1.9177 | 87.99692 | 23.92799 |
1.05 | 21.4 | 1.75895 | 76.43031 | 24.70351 |
1.0538 | 19.7 | 1.7399 | 77.4509 | 25.58456 |
1.0355 | 28 | 1.778 | 83.1208 | 26.29337 |
1.0486 | 22.1 | 1.778 | 80.85284 | 25.57595 |
1.0503 | 21.3 | 1.78435 | 73.93556 | 23.22166 |
1.0384 | 26.7 | 1.82245 | 79.49206 | 23.93385 |
1.0607 | 16.7 | 1.75895 | 71.66759 | 23.16412 |
1.0529 | 20.1 | 1.84785 | 80.39925 | 23.54608 |
1.0671 | 13.9 | 1.8288 | 81.19303 | 24.27651 |
1.0404 | 25.8 | 1.8796 | 86.63614 | 24.5227 |
1.0575 | 18.1 | 1.83515 | 85.04857 | 25.25363 |
1.0358 | 27.9 | 1.8923 | 93.66682 | 26.15808 |
1.0414 | 25.3 | 1.8161 | 84.02799 | 25.47678 |
1.0652 | 14.7 | 1.74625 | 72.68818 | 23.83696 |
1.0623 | 16 | 1.69545 | 68.71924 | 23.90608 |
1.0674 | 13.8 | 1.6891 | 73.02837 | 25.59652 |
1.0587 | 17.5 | 1.7018 | 75.74993 | 26.15563 |
1.0373 | 27.2 | 1.74625 | 80.51265 | 26.40288 |
1.059 | 17.4 | 1.72085 | 69.05944 | 23.32046 |
1.0515 | 20.8 | 1.86055 | 87.20313 | 25.19123 |
1.0648 | 14.9 | 1.77165 | 74.95614 | 23.88094 |
1.0575 | 18.1 | 1.8161 | 77.90449 | 23.62017 |
1.0472 | 22.7 | 1.7907 | 77.67769 | 24.22427 |
1.0452 | 23.6 | 1.86055 | 89.3577 | 25.81364 |
1.0398 | 26.1 | 1.69545 | 71.214 | 24.77396 |
1.0435 | 24.4 | 1.7653 | 76.31692 | 24.48972 |
1.0374 | 27.1 | 1.77165 | 84.36818 | 26.8796 |
1.0491 | 21.8 | 1.79705 | 75.63653 | 23.42131 |
1.0325 | 29.4 | 1.8796 | 85.16197 | 24.10543 |
1.0481 | 22.4 | 1.80975 | 76.31692 | 23.30149 |
1.0522 | 20.4 | 1.905 | 96.50178 | 26.59165 |
1.0422 | 24.9 | 1.8034 | 80.17245 | 24.65137 |
1.0571 | 18.3 | 1.7653 | 78.58488 | 25.2175 |
1.0459 | 23.3 | 1.72085 | 75.74993 | 25.57974 |
1.0775 | 9.4 | 1.83515 | 72.46138 | 21.5161 |
1.0754 | 10.3 | 1.9685 | 85.3434 | 22.02415 |
1.0664 | 14.2 | 1.79705 | 70.76041 | 21.91139 |
1.055 | 19.2 | 1.84785 | 94.57401 | 27.69736 |
1.0322 | 29.6 | 1.77165 | 93.66682 | 29.84214 |
1.0873 | 5.3 | 1.8415 | 65.2039 | 19.22782 |
1.0416 | 25.2 | 1.78435 | 101.1511 | 31.76951 |
1.0776 | 9.4 | 1.7526 | 69.05944 | 22.48316 |
1.0542 | 19.6 | 1.8923 | 109.656 | 30.62333 |
1.0758 | 10.1 | 1.83515 | 66.22449 | 19.66416 |
1.061 | 16.5 | 1.70815 | 71.1006 | 24.36808 |
1.051 | 21 | 1.8669 | 90.83187 | 26.0613 |
1.0594 | 17.3 | 1.91135 | 77.79109 | 21.29362 |
1.0287 | 31.2 | 1.7526 | 93.32663 | 30.38365 |
1.0761 | 10 | 1.83515 | 82.78061 | 24.5802 |
1.0704 | 12.5 | 1.74625 | 61.91536 | 20.30419 |
1.0477 | 22.5 | 1.8161 | 80.39925 | 24.37656 |
1.0775 | 9.4 | 1.83515 | 68.60585 | 20.37127 |
1.0653 | 14.6 | 1.8542 | 88.9041 | 25.85882 |
1.069 | 13 | 1.74625 | 83.57439 | 27.40693 |
1.0644 | 15.1 | 1.7907 | 63.50293 | 19.80378 |
1.037 | 27.3 | 1.8288 | 99.22333 | 29.66753 |
1.0549 | 19.2 | 1.87325 | 98.42954 | 28.05007 |
1.0492 | 21.8 | 1.7272 | 75.40973 | 25.27797 |
1.0525 | 20.3 | 1.83515 | 101.9449 | 30.27069 |
1.018 | 34.3 | 1.7653 | 103.5325 | 33.22306 |
1.061 | 16.5 | 1.7653 | 78.35808 | 25.14472 |
1.0926 | 3 | 1.72085 | 69.05944 | 23.32046 |
1.0983 | 0.7 | 1.6637 | 57.03924 | 20.60742 |
1.0521 | 20.5 | 1.8034 | 80.39925 | 24.7211 |
1.0603 | 16.9 | 1.8161 | 79.94566 | 24.23904 |
1.0414 | 25.3 | 1.82245 | 102.8521 | 30.9672 |
1.0763 | 9.9 | 1.75895 | 65.88429 | 21.29486 |
1.0689 | 13.1 | 1.7018 | 68.49245 | 23.6497 |
1.0316 | 29.9 | 1.8161 | 109.4292 | 33.17827 |
1.0477 | 22.5 | 1.75895 | 84.93517 | 27.45242 |
1.0603 | 16.9 | 1.8923 | 106.4808 | 29.7366 |
1.0387 | 26.6 | 1.88595 | 99.45013 | 27.9605 |
1.1089 | 0 | 1.7272 | 53.7507 | 18.01768 |
1.0725 | 11.5 | 1.70815 | 66.11109 | 22.65804 |
1.0713 | 12.1 | 1.77165 | 72.23458 | 23.01385 |
1.0587 | 17.5 | 1.88595 | 77.3375 | 21.74352 |
1.0794 | 8.6 | 1.8161 | 75.97672 | 23.03568 |
1.0453 | 23.6 | 1.88595 | 105.5736 | 29.68212 |
1.0524 | 20.4 | 1.8288 | 95.48119 | 28.54864 |
1.052 | 20.5 | 1.8415 | 91.73906 | 27.05271 |
1.0434 | 24.4 | 1.73355 | 83.91459 | 27.92317 |
1.0728 | 11.4 | 1.75895 | 69.39963 | 22.43108 |
1.014 | 38.1 | 1.9304 | 110.7899 | 29.73073 |
1.0624 | 15.9 | 1.7907 | 87.77012 | 27.37165 |
1.0429 | 24.7 | 1.89865 | 101.9449 | 28.27976 |
1.047 | 22.8 | 1.84785 | 73.82216 | 21.61988 |
1.0411 | 25.5 | 1.73355 | 81.64663 | 27.16849 |
1.0488 | 22 | 1.7526 | 70.87381 | 23.07386 |
1.0583 | 17.7 | 1.8161 | 76.20352 | 23.10444 |
1.0841 | 6.6 | 1.84785 | 75.86332 | 22.21767 |
1.0462 | 23.6 | 1.7145 | 77.4509 | 26.34823 |
1.0709 | 12.2 | 1.78435 | 80.85284 | 25.39424 |
1.0484 | 22.1 | 1.75895 | 68.03886 | 21.99126 |
1.034 | 28.7 | 1.8161 | 90.94527 | 27.57405 |
1.0854 | 6 | 1.8796 | 83.461 | 23.62396 |
1.0209 | 34.8 | 1.77165 | 101.1511 | 32.22662 |
1.061 | 16.6 | 1.8542 | 94.68741 | 27.54096 |
1.025 | 32.9 | 1.6637 | 75.29633 | 27.20344 |
1.0254 | 32.8 | 1.8415 | 88.45051 | 26.08296 |
1.0771 | 9.6 | 1.78435 | 72.80158 | 22.8655 |
1.0742 | 10.8 | 1.79705 | 72.46138 | 22.43811 |
1.0829 | 7.1 | 1.7272 | 63.72973 | 21.36273 |
1.0373 | 27.2 | 1.8923 | 98.08935 | 27.39314 |
1.0543 | 19.5 | 1.82245 | 76.31692 | 22.97786 |
1.0561 | 18.7 | 1.79705 | 88.33711 | 27.35413 |
1.0543 | 19.5 | 1.8542 | 78.35808 | 22.79138 |
1.0678 | 13.6 | 1.77165 | 67.69866 | 21.56871 |
1.0819 | 7.5 | 1.778 | 70.08002 | 22.16821 |
1.0433 | 24.5 | 1.82245 | 90.37828 | 27.21152 |
1.0646 | 15 | 1.75895 | 70.08002 | 22.65099 |
1.0706 | 12.4 | 1.7907 | 69.51303 | 21.67807 |
1.0399 | 26 | 1.83515 | 104.3262 | 30.97778 |
1.0726 | 11.5 | 1.7145 | 73.36857 | 24.95945 |
1.0874 | 5.2 | 1.70815 | 64.52351 | 22.11393 |
1.074 | 10.9 | 1.74625 | 81.53323 | 26.73756 |
1.0703 | 12.5 | 1.69545 | 57.37943 | 19.96118 |
1.065 | 14.8 | 1.73355 | 76.88391 | 25.58366 |
1.0418 | 25.2 | 1.88595 | 90.03809 | 25.3143 |
1.0647 | 14.9 | 1.7653 | 79.15187 | 25.39944 |
1.0601 | 17 | 1.7399 | 76.09012 | 25.13505 |
1.0745 | 10.6 | 1.67005 | 67.01827 | 24.02892 |
1.062 | 16.1 | 1.82245 | 82.66721 | 24.88984 |
1.0636 | 15.4 | 1.8161 | 79.60546 | 24.13589 |
1.0384 | 26.7 | 1.70815 | 73.36857 | 25.14537 |
1.0403 | 25.8 | 1.7145 | 71.5542 | 24.34222 |
1.0563 | 18.6 | 1.7145 | 76.54371 | 26.03961 |
1.0424 | 24.8 | 1.83515 | 86.86294 | 25.79238 |
1.0372 | 27.3 | 1.7653 | 99.40477 | 31.89849 |
1.0705 | 12.4 | 1.7653 | 70.42022 | 22.5975 |
1.0316 | 29.9 | 1.67005 | 86.06915 | 30.85948 |
1.0599 | 17 | 1.67005 | 57.83303 | 20.73562 |
1.0207 | 35 | 1.73355 | 101.8315 | 33.88515 |
1.0304 | 30.4 | 1.8288 | 106.254 | 31.76968 |
1.0256 | 32.6 | 1.84785 | 103.3057 | 30.25456 |
1.0334 | 29 | 1.7399 | 90.49168 | 29.89235 |
1.0641 | 15.2 | 1.75895 | 70.53361 | 22.7976 |
1.0308 | 30.2 | 1.7907 | 97.74916 | 30.48368 |
1.0736 | 11 | 1.7018 | 60.89478 | 21.02631 |
1.0236 | 33.6 | 1.77165 | 91.17207 | 29.04731 |
1.0328 | 29.3 | 1.6764 | 84.70838 | 30.14193 |
1.0399 | 26 | 1.7907 | 86.52274 | 26.98265 |
1.0271 | 31.9 | 1.778 | 94.12042 | 29.77285 |
Exploratory data analyses (EDA)
Various data patterns may be observed and explored using different types of graphical tools for plotting variables. Which of the following graphs are more or less likely to demonstrate visually significant grouping differences?
Conclusions
Practice problems
See also
References
Translate this page: