Conceptual Questions:1. Suture anchors are used to reattach tendons or ligaments to bone. You are creating ananchor system for the ACL that involves two suture anchors on the distal end of the joint.You plan a study that compares this new anchor system to the currently used anchorsystem. Based on your experimental study, you have two outcome measures: i) the failurestatus of the suture during an experimental protocol and ii) the ultimate tensile failureload. Complete the following tasks: A) Would the two experimental groups in Figure liibe considered independent or disjoint? Is the outcome measure in Figure 1i consideredindependent or disjoint? Provide a brief explanation for eachFigure li:Number ofOccurrences10Figure lii:40Failure Load (kN)30201050Current anchorsFailure ■ No failureCurrent anchorsExperimental anchorsExperimental anchors

Disjoint: Subjects in disjoint groups cannot simultaneously be part of both groups.Independent: In…

Answered: Conceptual Questions: 1. Suture anchors…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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3. You want to determine the effectiveness of a novel cancer therapy, RS7, in treating lung cancer. You cultured lung cancer microtissues in cell culture plates with equal numbers of cells per well. You exposed plate 1 to the novel drug and left plate 2 untreated (control). You analyzed both plates using flow cytometry and propidium iodide to identify live and dead cells. The results below represent the number of viable cells. Using a t-test, determine whether RS7 reduces the viability of lung cancer cells. Plate 1 (RS7): X1 = 65,434 X2 = 70,250 Plate 2 (control): X'1 = 80,760 X'2 = 78,562 X3= 63,962 X'3=81,435 A) State the null hypothesis (Ho): X4= 61,030 X'4 = 75,650 X5= 60,572 X'5 = 77,112
b) Suppose you are given the following information for an OLS regression: Σχι X; Y = 830102,T = 22,x=416.5, y = 86.65, x = 3919654, RSS = 130.6 i) Calculate the ordinary least square regression line. Calculate SE (a) and SE (B) Perform the hypothesis test such that Ho: a = -60 versus H₁: α = -60 Perform the hypothesis test such that Ho: P = 0.4 versus H₁: B = 0.4 In both cases use a significance of 5%. ii) iii) iv)
6 A valve manufacturer produces a butterfly valve composed of two semicircular plates on acommon spindle that is used to permit flow in one direction only (seen here:http://en.wikipedia.org/wiki/Butterfly_valve). The semicircular plates are supplied by a vendorwith specifications that the plates be 2.37 millimeters thick and have a tensile strength of fivepounds per millimeter. A random sample of 20 such plates is taken. Electronic calipers are usedto measure the thickness of each plate. A universal testing machine was used to test the tensilestrength. The sample data are found in homework 5.xlsx.a. Find point estimates of the thickness and tensile strength data. Compare with thespecifications.b. Construct a 95% confidence interval for mean thickness. Draw conclusions regarding thespecification relative to the confidence interval.c. Construct a 95% confidence interval for mean tensile strength. Draw conclusionsregarding the specification relative to the confidence interval.d. Construct…
After ingesting 15 mL of 95% alcohol, the blood alcohol level of a 75 kg adult male rises rapidly to a maximum level then gradually decreases over time. Measurements of the subject's blood alcohol level at time t (in minutes) since the maximum blood alcohol level was observed gave the following results: Time t (in minutes) Blood alcohol level, B (in mg/L) 10 25 60 70 90 150 160 130 70 60 40 20 a) Using least squares regression, determine an equation of the form B= Be-kt that best fits the relationship shown. You do not need to graph the data. (Note any transformations you have applied to your data: x→, y→, round the values that appear in your final equation to three significant figures, and use the correct variable names...not x and y.)| b) Using your equation from part a), estimate the time t at which the subject's blood alcohol level will be 90 mg/L? Round your answer to the nearest minute.
TABLE BELOW SHOWS THE REGRESSION ESTIMATION RESULT FOR THE PRICE AND DEMAND VARIABLES INCLUDED IN THE PREVIOUS QUESTION. PLEASE ESTIMATE THE DEMAND OF THE PRODUCT WHEN THE PRICE IS 15. PLEASE EXPLAIN YOUR PEASON) Intersection (c) Price A32.13 OC685 0.451.5 Coefficients Standard t Stat Error 2,142429 14,04948 0,000781 0,206155 -7,5186 0,004876 30,1 -1,55 P-Value
Find the best predicted value of y corresponding to the given value of x. 44) Six pairs of data yield r = 0.444 and the regression equation y = 5x + 2. Also, y = 18.3. What is the best predicted value of y for x = 5? A) 4.22 B) 18.3 C) 27 D) 93.5 44)
You are testing the null hypothesis that there is no linear relationship between two variables, X and Y. From your sample of n = 10, you determine that r = 0.80. a) What is the value of the t test statistic t STAT ? b) At the a = 0.05 level of significance, what are the critical values? c) Based on your answers to (a) and (b), what statistical decision should you make?
Solve the exercise. (In the other image, this is the correct answer, just to check)
An experiment to determine the effect of four different types of engine oil (A, B, C, and D) on the rolling friction coefficient of a car speed has been conducted. Three brands of car (Honda, Toyota, and Mazda) were chosen, and each engine oil was tested twice on each car, producing the following ANOVA output in Figure 2. i) How many treatments involved? Write down all the treatments ii) Identify the number of replication for each treatment. iii) Based on the ANOVA table above, find the values of W, X, Y and Z. iv) Test the interaction effect on rolling friction coefficient of car speed between the four different types of engine oil and the three different brands of car. v) Do we need to test for marginal effect? Give a reason.
We wish to test an effect of a drug that claimed to improves the patients with 80% of chance. The drug is given to 20 patients and we observed the number Y of people who improved. The hypothesis is Ho :p = 0.8 vs Hị : p< 0.8. Use the rejection region RR = {y< 12} and answer question a-e.
A new design for the braking system on a certain type of car has been proposed. For the current system, the true average braking distance at 40 mph under specified conditions is known to be 120 ft. It is proposed that the new design be implemented only if sample data strongly indicates a reduction in true average braking distance for the new design. (a) Define the parameter of interest. O μ = true average braking distance for the new design O μ = true average braking distance for the old design Op = true proportion of cars whose braking distances did not reduce Op = true proportion of cars whose braking distances reduced State the relevant hypotheses. O Ho: 120 H₂: > 120 ⒸHO: P = 120 H₂: P = 120 ⒸH₂: p = 120 Ha: p < 120 Ho: = 120 Ha: # < 120 ⒸH₂ = 120 H₂H 120 (b) Suppose braking distance for the new system is normally distributed with = 11. Let X denote the sample average braking distance for a random sample of 36 observations. Which values of x are more contradictory to H than 117.2?…
Josh ran an experiment to test optimum power and time settings for microwave popcorn. His goal was to deliver popcorn with fewer than 11% of the kernels left unpopped, on average. He determined that power 9 at 4 minutes was the best combination. Complete parts a) and b) below. a) He concluded that this popping method achieved the goal of fewer than 11% of the kernels left unpopped. If it really does not work that well, what kind of error did Josh make? Type Il error Type I error b) To be sure that the method was successful, he popped 8 more bags of popcorn (selected at random) at this setting. All were of high quality, with the percentages of unpopped kernels shown below. 12.4, 2.9, 8.6, 8.1, 13.4, 3.2, 2.7, 9.5 O Does this provide evidence that he met his goal of an average of fewer than 11% unpopped kernels? Assume a = 0.05. Choose the correct null and alternative hypotheses. A. Ho μ= 11 HA: µ 11 O F. Ho: µ> 11 HA: H= 11 Е. Но: <11 HẠ: µ= 11 %3D Calculate the test statistic. t=…

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