The following table shows the length, in centimeters, of the humerus and the total wingspan, in centimeters, of several pterosaurs, which are extinct flying reptiles. (A graphing calculator is recommended. Pterosaur Data Humerus, x Wingspan, y Humerus, x Wingspan, y 25 589 26 596 30 598 32 599 24 536 22 532 21 529 20 473 18 465 15 443 1.4 38 1.1 35 1.0 35 0.9 28 0.8 24 (a) Find the equation of the least-squares regression line for the data. Round constants to the nearest hundredth. (b) Use the equation from part (a) to determine, to the nearest centimeter, the projected wingspan of a pterosaur if its humerus is 50 centimeters. cm

Please answer all these questions and label, data included: Size($) Rent(sq.feet) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750   10. Based on all of the above questions, what will you conclude about the relationship between house size and rent price?       11. Construct a 95% confidence interval estimate of the population slope, β1.         12. Construct a 95% confidence estimate of the mean renting cost of a house that is 2000 square feet.         13. Construct a 95% prediction interval of the renting cost of an individual house that is 2000 square feet.

Please answer questions 8 and 9 fully, data included: Size($) Rent(sq.feet) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750 A real estate agent wishes to examine the relationship between the selling price of a home (measured in thousands of dollars) and its size (measured in square feet). In particular she wants to assess if the size of the home can accurately predict the house’s selling price.

Please answer question 9 fully, data included: Size($) Rent(sq.feet) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750 A real estate agent wishes to examine the relationship between the selling price of a home (measured in thousands of dollars) and its size (measured in square feet). In particular she wants to assess if the size of the home can accurately predict the house’s selling price.

Please see the attached images for problem data. Appears that I got the problem wrong so  can use some great help!   Thanks   Data:   Program Per-Year Tuition ($) Mean Starting Salary Upon Graduation ($) 63724 153070 66630 155000 68013 146993 68300 145146 66412 139879 66543 150987 67671 150702 69927 148214 64602 133363 63552 146360 67772 146066 60752 148017 62369 141289 57816 136211 55621 122130 56385 118657 56937 128143 50884 130983 53195 131361 51351 120554 45123 114333 48225 111894 49798 109446 46568 106959 39254 81908 47213 80788 47633 99916 51018 79430 37216 88340 32877 76172 42643 73728 40997 52291 48807 66277 34080 103181 24201 56567 42467 79381 39070 52931

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. Use the information to estimate the slope of the least squares regression line. Enter your answer using three…

Please see image for Question.

The data on the right represent the number of live multiple-delivery births (three or more babies) in a particular year for women 15 to 54 years old. Use the data to complete Number of Multiple parts (a) through (d) below. Age 15-19 Births 89 20-24 515 25-29 1628 30-34 2837 35-39 40-44 1849 373 45-54 118 (a) Delemne une provavmy uiat a Tanuomy seiecieu muupie DiruTIOr WUmen TO-04 years uiu nvoiveu a IOuier JU U 39 years OIu. P(30 to 39) = 1 (Type an integer or decimal rounded to three decimal places as needed.) (b) Determine the probability that a randomly selected multiple birth for women 15-54 years old involved a mother who was not 30 to 39 years old. P(not 30 to 39) = (Type an integer or decimal rounded to three decimal places as needed.) (c) Determine the probability that a randomly selected multiple birth for women 15-54 years old involved a mother who was less than 45 years old. P(less than 45) = (Type an integer or decimal rounded to three decimal places as needed.)

ExQm Score Oata 76 69 64 75 70 80 90 86 77 79 82 96 51 64 95 6.2 76 65 68 74 Oc Mahe a box- and whiskar plot d alculus data Exam

3. Which box plot has the largest interquartile range?