Use a dot plot to display the data, which represent the systolic blood pressures (in millimeters of mercury) of 24 patients at a doctor's office. Describe any patterns. 120 135 140 145 130 150 120 170 145 125 135 110 160 180 200 150 200 135 200 120 130 170 165 140 Which dot plot below displays the data? O A. OC. 105 115 125 135 145 155 165 175 185 195 205 105 115 125 135 145 155 165 175 185 195 205 What best describes the data? G OA. Most of the values are greater than 150. B. Most of the values are between 120 and 150. OC. The values are evenly spread from 110 to 200. D. Most of the values are between 140 and 180. COLL B. O D. 105 115 125 135 145 155 165 175 185 195 205 105 115 125 135 145 155 165 175 185 195 205 o

shape ?

A sample of blood pressure measurements is taken for a group of​ adults, and those values​ (mm Hg) are listed below. The values are matched so that 10 subjects each have a systolic and diastolic measurement. Find the coefficient of variation for each of the two​ samples; then compare the variation. Systolic 118 127 160 94 155 122 116 137 124 119   Diastolic 82 77 72 50 89 89 59 65 72 82

The height of bedridden patients is often estimated from the length of the patient's ulna, the distance between the point on the elbow and the prominent bone on the wrist. Eight men over the age of 65 had both their height (in centimeters) and the length of their ulna (in centimeters) measured. The data are given in the table below. Ulna length (cm) 20 23 24 26 27 29 30 31 Height (cm) 160 163 166 168 171 178 182 186 Let x denote a patient's ulna length (in cm) and y denote the patient's height (in cm). Assume that the population distributions for both ulna length and height are approximately normal. The following summary measures were obtained from the data. X = 26.25, ỹ = 171.75, SSxx = 99.5, SSyy= 609.5, SSxy= 238.5 ху We wish to find the least squares regression line for the data in this table using ulna length as an independent variable and height as a dependent variable. Estimate the y-intercept of the least squares regression line. Enter your answer using three decimal places.