The data in the attached image represents blood pressure based on a new trial medication used in an experiment involving a total of 50 male and female subjects.  There were two levels of treatment: 0 = placebo and 1 = treatment group. Family History Blood Pressure = Fam-Hist-BP; from the paternal side = PS; from the maternal side = MS; from both sides = BS; none on both sides or not known = N.; Blood pressure before the experiment = BP-Before-Exp; Blood pressure after the experiment = BP-After-Exp. Task: Construct a histogram to represent the family BP history, the subjects' BP before treatment and the subjects' BP after treatment.

The data in the attached image represents blood pressure based on a new trial medication used in an experiment involving a total of 50 male and female subjects.  There were two levels of treatment: 0 = placebo and 1 = treatment group. Family History Blood Pressure = Fam-Hist-BP; from the paternal side = PS; from the maternal side = MS; from both sides = BS; none on both sides or not known = N.; Blood pressure before the experiment = BP-Before-Exp; Blood pressure after the experiment = BP-After-Exp. Task: Find the mean and standard deviation for the family history group, the before treatment group, and the after treatment group.

The data in the attached image represents blood pressure based on a new trial medication used in an experiment involving a total of 50 male and female subjects.  There were two levels of treatment: 0 = placebo and 1 = treatment group. Family History Blood Pressure = Fam-Hist-BP; from the paternal side = PS; from the maternal side = MS; from both sides = BS; none on both sides or not known = N.; Blood pressure before the experiment = BP-Before-Exp; Blood pressure after the experiment = BP-After-Exp. Task: Generate at least two different cross tabulations.

Anemia (low healthy blood cells or hemoglobin) has an important role in exercise performance. However, the direct link between rapid changes of hemoglobin and exercise performance is still unknown. A study investigated 18 patients with a blood disorder (beta-thalassemia). Participants in the study performed an exercise test before and the day after receiving a blood transfusion. Data are given in the table. HB = Hemoglobin RER = Respiratory exchange ID Change in HB Obese RER > 1.1 ratio No No 1 -1.4 No -1.5 No Yes No Yes 3 -2 No 4 -2.1 No -1.9 Yes Yes No -1.6 -1.8 -0.8 6 7 No Yes No Yes 8 9. -1 No No -1.2 No Yes 10 11 No No -0.8 -1.5 12 Yes No No Yes 13 14 -1.4 -2.6 -1.7 No No Yes Yes 15 Yes No Yes Yes 16 -2.6 No 17 18 -2.7 -1.5 No

The feeding behavior of black bream (a type of fish) spawned in aquariums was studied in Brain, Behavior and Evolution (Apr. 2000). Zoologists recorded the number of aggressive strikes of two black bream feeding at the bottom of the aquarium in the 10 -minute period following the addition of food. The number of strikes and age of the fish (in days) were recorded approximately each week for nine weeks, as shown in the table below. ITT Week Number of Strikes Age of Fish (days) 1 85 120 2 63 136 3 34 150 4 39 155 58 162 6 35 169 7 57 178 8 12 184 15 190 a. Construct a scatterplot of the data, with number of strikes on the y -axis and age of the fish on the x -axis. b. Examine the scatterplot of part a. Do you detect a trend?

Blood cocaine concentration (mg/L) was determinedboth for a sample of individuals who had died fromcocaine-induced excited delirium (ED) and for a sampleof those who had died from a cocaine overdose withoutexcited delirium; survival time for people in bothgroups was at most 6 hours. The accompanying datawas read from a comparative boxplot in the article“Fatal Excited Delirium Following Cocaine Use” (J.of Forensic Sciences, 1997: 25–31). ED 0 0 0 0 .1 .1 .1 .1 .2 .2 .3 .3.3 .4 .5 .7 .8 1.0 1.5 2.7 2.83.5 4.0 8.9 9.2 11.7 21.0Non-ED 0 0 0 0 0 .1 .1 .1 .1 .2 .2 .2.3 .3 .3 .4 .5 .5 .6 .8 .9 1.01.2 1.4 1.5 1.7 2.0 3.2 3.5 4.14.3 4.8 5.0 5.6 5.9 6.0 6.4 7.98.3 8.7 9.1 9.6 9.9 11.0 11.512.2 12.7 14.0 16.6 17.8 a. Determine the medians, fourths, and fourth spreadsfor the two samples.b. Are there any outliers in either sample? Any extremeoutliers?c. Construct a comparative boxplot, and use it as abasis for comparing and contrasting the ED andnon-ED samples.

(b) In various places in this module, data on the silver content of coins minted in the reign of the twelfth-century Byzantine king Manuel I Comnenus have been considered. The full dataset is in the Minitab file coins.mwx. The dataset includes, among others, the values of the silver content of nine coins from the first coinage (variable Coin1) and seven from the fourth coinage (variable Coin4) which was produced a number of years later. (For the purposes of this question, you can ignore the variables Coin2 and Coin3.) In particular, in Activity 8 and Exercise 2 of Computer Book B, it was argued that the silver contents in both the first and the fourth coinages can be assumed to be normally distributed. The question of interest is whether there were differences in the silver content of coins minted early and late in Manuel’s reign. You are about to investigate this question using a two-sample t-interval. (i) Using Minitab, find either the sample standard deviations of the two variables…

A statistical program is recommended. A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. Repair Time in Hours 2.9 3.0 4.8 1.8 2.7 4.9 4.6 4.8 4.4 4.5 Months Since Last Service 2 6 8 3 2 7 9 8 4 6 Type of Repair Repairperson Electrical Mechanical Electrical Mechanical Electrical Electrical Mechanical Mechanical Electrical Electrical Dave Newton Dave Newton Bob…

A statistical program is recommended. A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. ŷ = Repair Time in Hours 2.9 3.0 ŷ = 4.8 1.8 2.4 4.9 4.7 4.8 4.4 4.5 Months Since Last Service 2 6 8 3 2 7 9 8 4 6 Type of Repair Electrical Mechanical Electrical Mechanical Electrical Electrical Mechanical Mechanical Electrical Electrical Repairperson Dave Newton Dave…