How many false positives were there among these 189 people? Explain the meaning of a false positive for the person tested. CHECK YOUR UNDERSTANDINGHigh intracranial pressure(inside the skull) typically is aresult of an injury to the headand can be very dangerous.A screening test for highintracranialpressure wasproposed many years ago,based on the data in thefollowing observations. Thissimple and non-invasive testinvolves observing the retinalvein to see if it is pulsating.Pulsation is normal and so would be considered a negative test result.Pulsation AbsentPulsation PresentTotal(Positive Test)(Negative Test)High Intracranial Pressure(Condition Present)4343Normal Intracranial Pressure18128146(Condition Absent)Total61128189Sources: B. E. Levin "The Clinical Significance of Spontaneous Pulsations of the Retinai Vein Archives of NeurolonyVol. 35, 1978 pp. 37-40, www.cebm.netindex aspxPor1042USPck BatyMeGrawI...

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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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A severe storm has an average peak wave height of 16.4 feet for waves hitting the shore. Suppose that a storm is in progress with a severe storm class rating. Let us say that we want to set up a statistical test to see if the wave action (i.e., height) is dying down or getting worse. If you wanted to test the hypothesis that the waves are dying down, what would you use for the alternate hypothesis? Is the P-value area on the left, right, or on both sides of the mean? a. H1 : μ is less than 16.4 feet; the P-value area is on the right of the mean b. H1 : μ is not equal to 16.4 feet; the P-value area is on the right of the mean c. H1 : μ is not equal to 16.4 feet; the P-value area is on the left of the mean d. H1 : μ is greater than 16.4 feet; the P-value area is on the right of the mean e. H1 : μ is less than 16.4 feet; the P-value area is on the left of the mean
Please help me understand how to properly solve and understand. A researcher wanted to test if avid readers are more likely to wear glasses than those who read less frequently. 300 people were selected at random. Results are displayed in photo. The researcher wishes to test that the null hypothesis determines there is no association between the amount of reading and wearing glasses. Question: Under null hypothesis, determine the numerical value of the chi-square statistic.
Dependent or Independent? Listed below are systolic blood pressure measurements (mm Hg) taken from the right and left arms of the same woman at different times (based on data from “Consistency of Blood Pressure Differences Between the Left and Right Arms,” by Eguchi et al., Archives of Internal Medicine, Vol. 167). Are the data dependent or independent?
am i right ? pls help ill rate
The so-called PEFR score (Peak Expiratory Flow Rate) is a measure used to measure lung function in asthma patients. The higher the value, the better the lungs function. The theory has long been that walking in cold weather has a positive effect on lung function. To investigate this theory, the Directorate of Health decided to conduct a study in which six asthma patients were randomly selected and allowed to walk outside in cold weather for one hour. Their PEFR score was measured before the walk and again after the walk, one hour later. The data can be seen below. Asthma patient number PEFR score before PEFR score after 1 300 312 2 201 342 3 232 340 4 312 388 5 220 296 6 256 254 PEFR scores in asthma patients can be expected to follow normal distribution. Justify which test is appropriate for this data to see if walking in cold weather for an hour has a positive effect on the lung function of asthma patients. Use α = 0.05. Present the hypotheses, examine the hypothesis…
Heat flow is the passage of thermal energy from a hot to a cold body. This phenomenon is of particular interest to engineers, who attempt to understand and control the flow of heat through the use of thermal insulation and other devices. The data below were taken from heat flow gauge readings for an industrial process over 10 equally spaced time intervals. A concern is that the process may be cooling down as time progresses. One way to check this statistically is to compare the measurements for the first 5 time periods to the measurements for the last 5 time periods. You may assume that heat flow is approximately normal for each group. Time period 1 (Group 1): 9.273, 9.262, 9.243, 9.283, 9.270Time period 2 (Group 2): 9.240, 9.292, 9.284, 9.279, 9.258 Unless otherwise stated, give your answers to three decimal places. Construct a 95% confidence interval for the difference in mean heat flow. Give your answers to three decimal places. Use t∗=2.352t∗=2.352.( , ) Conduct a hypothesis…
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Interpret the estimated education coefficient. Is the estimate of the constant statistically significant at the 5% level? Explain how you reached this conclusion. Imagine you want to test with an F-test whether the effect of married and nonwhite are jointly significantly different from zero. Write down the null and alternative hypothesis for such a test
A specimen of connective tissue (collagen) can be obtained from a beef steak. The temperature at which the collagen shrinks can be determined. A tender piece of meat tends to have a low collagen shrinkage temperature. So, the lower shrinkage temperature, the more tender the meat.It is believed that electrical stimulation of a beef carcass could improve the tenderness of the meat. In one study of this effect, beef carcasses were split in half; one side (half) was subjected to a brief electrical current and the other side was an untreated control. For each side, a steak was cut and tested in various ways for tenderness. In one test, the experimenter obtained a specimen of the connective collagen tissue from the steak and determined the temperature at which the tissue would shrink. The experimenter wishes to prove that electrical stimulation tends to improve the tenderness of the meat. The raw data are found in the table below. Let ? = 0.01. Table 1: Collagen Shrinkage Temperature…
Describe the difference between parametric statistics and non-parametric statistics. What is an example of a test for each form of statistics?
A new cream that advertises that it can reduce wrinkles and improve skin was subject to a recent study. A sample of 4949 women over the age of 50 used the new cream for 6 months. Of those 4949 women, 3333 of them reported skin improvement(as judged by a dermatologist). Is this evidence that the cream will improve the skin of more than 6060% of women over the age of 50? Test using ?=0.05α=0.05. test statistics ?=z= rejection region ?>z>
A total of 30 subjects are measured both before and after an intervention. What are the degrees of freedom for a t-test assessing if the subjects improved over time?

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