For the following questions use data a. Create a scatterplot of the height x ver

Question

For the following questions use data

a. Create a scatterplot of the height x versus the leg length y. Is it linear?

b. Use calculator software to write a regression equation for the data set.

c. Graph the least squares regression line on the plot for part a.

Construct your graph using to points on your least squares regression line.

d. Determine the correlation coefficient and the coefficient of determination and interpret them in this situation in a sentence for each.

e. Find the residual when height is 71.

Conduct Hypothesis Test for correlation.

f. Write hypothesis.

g. Find the critical r at a significance of .05.

h. Find the test statistic.

i. Make a conclusion about the Null Hypothesis

j. Summarize with the Alternative Hypothesis.

646 APPENDIX B Data Set 1: Health Exam Results AGE is in years, HT is height (inches), WT is weight (pounds), WAIST is circumference (cm), PULSE is pulse rate (beats per minute), SYS is systolic blood pressure (mmHg), DIAS is diastolic blood pressure (mmHg), CHOL is cholesterol (mg), BMI is body mass index, LEG is upper leg length (cm), ELBow is elbow breadth (cm), WRIST is wrist breadth (cm), and ARM is arm circumference (cm). Data are from the U.S. Department of Health and Human Services National Center for Health Statistics, Third National Health and Nutrition Examination Survey. Male WT Waist Pulse SYS DIAS 58 70.8 90.6 25 78 22 66.2 44.2 07 32 79.3 88 68.7 75.8 87.7 72 28 67.6 152.6 87.1 69.2 66.8 92.4 83 66.5 35.0 78.8 67.2 103.3 26 72 68.3 75.2 89. 76 37 65.6 39.0 71 17 63.0 56.3 86.7 73 68.3 86.6 103.3 72 53 87 52 73.1 19 91.8 77 67.6 75.6 29 68.0 209.4 105.5 82 237 08.7 61.3 176.7 104.0 76.2 220.6 03.0 76 75 32 66.3 66.1 32 69.7 137,4 75.2 65.4 64.2 87.7 72 29 70.00 77.0 62.9 151.8 85.0 95 68.5 79.6 68.3 204.6 103.8 69.4 93.8 03.0 53 69.2 172.9 79 28 68.00 161.9 86.9 71.9 74.8 88.0 37 69.8 72.4 213.3 02.9 72 33 73.0 98.00 132 74 26 68.00 73.3 98. 88 116 214.5 107.5 125 84 137.1 119.5 56 89. 95.0 56 65.6 164.7 70.1 75 20 66.3 151.0 79.9 72 115 Text file names for males are MAGE, MHT, MWT, MWAST, MPULS, MSYS, MDIAS, MCHOL, MBMI, MLEG, MELBW, MWRST, MARM. Arm wrist Elbow BMI CHOL 7.7 6.4 42.5 23.8 522 7.6 6.2 40.2 23.2 27 5.8 32.7 7.3 24.6 44.4 740 5.9 33.4 7.5 26.2 42.8 6,0 30. 23.5 40.0 230 5.8 30.5 24.5 47.3 316 43.4 6.5 5.2 27.6 5.6 38.0 466 12 26.4 42 7.5 5.5 32.0 578 22.7 36.0 6,9 29.3 27.8 44.2 7.1 5.3 28 36.7 8.1 6,7 30.7 48.4 25.2 8.0 34.7 23.3 7.0 5.7 30.6 273 39.8 6.9 6.0 34.2 33 45.2 8.3 6.6 33.2 40.2 6.7 5.7 33.1 75 26.7 46.2 7,9 6.0 32.2 138 26.6 39.0 7.5 5.7 31.2 9.9 44.8 6.9 5.6 25.9 27.1 40.9 7.0 5.6 33.7 613 23.4 43. 7.5 5.2 762 27.0 38.0 7.4 5.8 32.8 41.0 6,8 5.7 31.0 690 30.9 46.0 7.4 6.1 36.2 31 28.3 7.2 6.0 89 42.7 6,6 5.9 957 24.6 40.5 7,3 5.7 32.9 339 23.8 44.2 7.8 6.0 27.4 7.0 28.7 47.2 5.9 26.2 48.2 7.8 6.0 26.4. 42.9 6.7 31.3 5.8 288 32. 42.8 8.2 5.9 76 9.6 7.1 27.9 5.3 20.7 42.6 6.6 5.3 649 6.0 26.9 34.5 6,1 656 25.6. 7.3 5,8 7.1 5.4

Explanation / Answer

. In your CensusAtSchool arbitrary example, discover the question about tallness, and the question about arm traverse, and enter both arrangements of twenty numbers as:
as a table in your exercise manual or
two sections in Excel, or
two separate records in your CAS adding machine
2. Make a disseminate plot, with stature as the autonomous variable (x) and arm traverse as the needy variable (y).
3. Make a line of best fit. Position your ruler on the diagram to take after the general pattern of the information, then move the ruler and decide a line so that around ten (half ) information focuses are over the line, and roughly ten (half) information focuses are beneath the line.
4. Finish the accompanying table by taking readings from your diagram utilizing the line of best fit. You may need to extrapolate (broaden your line) to find a few solutions.
Tallness (x)
160 cm
180 cm
250 cm
Arm Span (y)
150 cm
190 cm
5. Clarify why the numbers you have given in the table being referred to 4 are just expectations.
6. Give explanations behind what may influence the precision of your line of best fit.

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