The following is the breakdown of male patients with highblood pressure, high cholesterol, and diabetes at a medicalcenter by age. Each condition is independent and no patient onthe table has multiple conditions.25-2930-3940-4950-5960+High Blood0.010.040.050.080.22PressureHigh0.020.050.080.090.10CholesterolDiabetes0.010.050.050.080.07What is the probability a patient has high blood pressure if theyare between the age of 40-49?

e following is the breakdown of male patients with high pod pressure, high cholesterol, and diabetes at a medical hter by age. Each condition is independent and no patien e table has multiple conditions. 25-29 30-39 40-49 50-59 60+ gh Blood 0.01 0.04 0.05 0.08 0.22 essure gh 0.02 0.05 0.08 0.09 0.10 holesterol nbotos

e following is the breakdown of male patients with high pod pressure, high cholesterol, and diabetes at a medical hter by age. Each condition is independent and no patien e table has multiple conditions. 25-29 30-39 40-49 50-59 60+ gh Blood 0.01 0.04 0.05 0.08 0.22 essure gh 0.02 0.05 0.08 0.09 0.10 holesterol nbotos

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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ed weight (in kg) and total serum cholesterol (TSC in mg/dl) data for five men (n = 5). They tested for association between weight and TSC at 5% level of significance. weight, X TSC, Y X*X Y*Y X*Y 37 2.9 1369 8.41 107.3 50 0.7 2500 0.49 35.0 67 3.3 4489 10.89 221.1 70 4.2 4900 17.64 294.0 57 3.8 3249 14.44 216.6 SUM: 281 14.9 16507 51.87 874.0 What are the Null and Alternate hypotheses for this test? Clearly label your answers as HỌ or H1. (Do not use a numerical format. Both of your statements must be in sentence form, and say something about the weight
ol 106. Use the two scenarios presented in Figure 7.12 to answer the following question about the two sources of variability in ANOVA. 3.5 3.0 2.5 2.0 1.5 (i) HA: P₁ P2 ‡ P3 (iii) HA not all proportions are equal to this po 1.0 Figure 7.12: Within vs Between Variability in ANOVA onnisth Scenario A L (d) Recall that, O 2 H 3 2.05 2.10 2.15 2.20 2.25 2.30 2.35 (ii) Ho: M₁ M₂ = μ3 sans are (iv) HA: not all means are equal 720 qeaoluet alt sot mol 4 mobor 2924 (6) 2 3 4 gob za aim onbala (1) di batt (9) w-qodt fonqtotal bac o2 (6) (Troy ote12. (0) (a) Which scenario provides stronger evidence that the difference in factor level means represents true differences in the population means? Explain why in your own words. Scenario B 1 = stogol 05 O 1 oftaltete fest out of sulav gris I (b) Which scenario exhibits more variability within each factor level? Is this measured by SSError or SSFactor? Agulow (c) Which scenario exhibits more variability between each factor level? Is this measured by…
Data on weekday exercise time for 20 females, consistent with summary quantities given in the paper "An Ecological Momentary Assessment of the Physical Activity and Sedentary Behavior Patterns of University Students,"† are shown below. Female—Weekday 10.0 90.6 48.5 50.4 57.4 99.6 0.0 5.0 0.0 0.0 5.0 2.0 10.5 5.0 47.0 0.0 5.0 54.0 0.0 48.6 Calculate the values of the median and interquartile range. median: interquartile range: Interpret the values of the median and interquartile range. The median exercise time of indicates that half of the exercise times were below , and the remaining half were above . The interquartile range tells us that the middle fifty percent of exercise times had a range of .
A federal regulatory agency is investigating an advertised claim that a certain device can increase the gasoline mileage of cars (mpg). Ten such devices are purchased and installed in cars belonging to the agency. Gasoline mileage for each of the cars is recorded both before and after installation. The data are recorded here. Car 1 2 3 4 5 6 7 8 9 10 n x s Before (mpg) 19.1 29.9 17.6 20.2 23.5 26.8 21.7 25.7 19.5 28.2 10 23.22 4.25 After (mpg) 25.8 23.7 28.7 25.4 32.8 19.2 29.6 22.3 25.7 20.1 10 25.33 4.25 Change (mpg) 6.7 −6.2 11.1 5.2 9.3 −7.6 7.9 −3.4 6.2 −8.1 10 2.11 7.54 (a) The cars in the study appear to have grossly different mileages before the devices were installed. Use the change data to test whether there has been a significant gain in mileage after the devices were installed. Use ? = .05. H0: ?after ?before Ha: ?after ?before t = p-value
A researcher is conducting a test to see if handedness (right or left) affects the speed at which people perform a particular task. The researcher only knows the order in which the contestants finished. When the data are summarized (with R for right-handed and L for left-handed) the order of finishing (fastest to slowest) was: R, R, R, R, L, R, L, R, L, L Is there statistically significant evidence of an effect of handedness on the speed? Test statistic: The name of the statistical table, degrees of freedom (if appropriate), and the numerical value of the critical value for this test: P-value: Circle an appropriate conclusion: • There is significant evidence that left-handed contestants will finish the task faster. • We cannot reject the hypothesis that handedness has no effect on the time to finish the task. • There is significant evidence that right-handed contestants will finish the task faster.
Search and Rescue of DND provides various statistics on boating accidents in he Maritimes and B.C. These statistics include information on the wind speed at the time of the accident. The following chart includes information recorded for 184 accidents on both coasts for the same time period: Wind Conditions Accidents West Coast Accidents East Coast Nil 13 6 Light 74 42 Moderate 30 15 Strong or higher 3 1 a) Suppose xe indicates the wind conditions in the East Coast where xe=0 indicates Nil, xe=1 indicates Light, xe = 2 indicates moderate and xe = 3 indicates Strong or Storm. Also suppose that xw indicates the wind conditions on the West Coast and xt indicates…
The amounts (in dollars) paid by 20 students for textbooks during the fall term are given on the right. 22 44 29 55 27 35 25 51 64 62 24 47 62 59 35 42 27 53 65 59 Interval Frequency 10 - 19.99 20 - 29.99 30 - 39.99 40 - 49.99 50 - 59.99 60 - 69.99 Book Cost Does the histogram on the left represent this data? Yes А В С DE No A: 20 - 29.99 B: 30 - 39.99 C: 40 - 49.99 D: 50 - 59.99 E: 60 - 69.99
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Risk of Stroke (%) Age Pressure Smoker (Yes=1) 12 57 152 0 24 67 163 0 13 58 155 0 56 86 177 1 28 59 196 0 51 76 189 0 18 56 155 1 31 78 120 0 37 80 135 1 15 78 98 0 22 71 152 0 36 70 173 1 15 67 135 1 48 77 209 0 15 60 199 0 36 82 119 1 8 66 166 0 34 80 125 1 3 62 117 0 37 59 207 1 1. Interpret regression coefficient of Age (b1), Pressure (b2), and Smoker (b3), respectively. 2. The regression coefficient of Age (b1) are different in the estimated simple regression equation and estimated multiple regression equation. Can you explain why? 3. If we choose the significance level α=0.05, is the variable Smoker a significant factor in explaining the risk of a stroke? Explain.