The following table gives the lifetime in hours of 400 radio tubes of acertaln make. Find the mean lifetime of the radio tubes.Number of tubesLifetime(in hrs.)Less than 300Number oftubesLifetime(in hours)Less than 800265400209003241,0001,1001,20050060374116600700392194400

We want to find the mean lifetime of the radio tubes.

Answered: The following table gives the lifetime…

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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2. In an advertisement, a certain brand of shampoo is claiming that the use of this product will make the hair grow faster. It is known that the mean length of growing hair over thirty days is 2 cm Ho: Hị: Photo is taken from https://stylecaster.com/beauty/best- hair-growth-shampoos/
Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 44 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that o = 8.00 ml/kg for the distribution of blood plasma.
Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 50 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that ? = 7.20 ml/kg for the distribution of blood plasma.
For SRSWOR (N,n), find the ratio estimator of population mean. Show that the estimator is biased.
Use reg no 134 Q.1 From the set of data X having the values last number of your registration number as X1 is the last digit of your registration number, X2=X1+1, X3=X2+2 and X4=X3+3, then (5+5) I. Show that the sum of the deviations of the observations Xi's from their mean, is equal to zero. II. Show that sum of square of devotion form mean is minimum than the sum of squared devotion from any other arbitrary value
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Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. x days y km/100 71 76 31 92 203 14.2 19.6 5.8 11.2 35.9 (a) Verify that Ex = 473, Ey = 86.7, Ex = 61,451, Ey = 2033.69, Exy = 10995.7, and r 0.93868. %3D %3D %3D %3D Σχ 1 473 ΣΥ| 86.7 Ex2 61451 Ey2 2033.69 Exy 10995.7 r0.93868 (b) Use a 1% level of significance to test the claim p > 0. (Use 2 decimal places.) t 4.72 critical t 4.54 Conclusion Reject the null hypothesis, there is sufficient evidence that p > 0. O Reject the null hypothesis, there is insufficient evidence that p > 0. Fail to reject…
Glaucoma is a leading cause of blindness in the United States, N. Ehlers measured the difference in corneal thickness (in microns) between the two eyes of eight patients. Each patient had one eye that had glaucoma and one eye that was normal. The difference was measured as the corneal thickness of normal eye – corneal thickness of eye with Glaucoma. Corneal thickness is important because it can mask an accurate reading of eye pressure. Use ? = .05. Hypothesis: H0: μd=0Ha: μd≠0 Using output Test statistics : t=0.134P value=0.897 Degrees of freedom (df): df=7 Level of significance: α=0.05 Decision: P value > 0.05 thus we fails to reject null hypothesis. Question a)Write a report summarizing your findings. When writing the report consider that medical staff estimate that a difference of 4.5 microns or more could impact on their ability to interpret eye pressure correctly. b) Define for the hypothesis stated in part b) what a type 1 error and type 2 error would mean. Is it possible…
Mean for nunber 5 is 100
A researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.
Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both the number of births x per one thousand people in the population and the female life expectancy y (in years) are given. These data are displayed in the Figure 1 scatter plot. Also given is the product of the birthrate and the female life expectancy for each of the twelve countries. (These products, written in the column labelled "xy", may aid in calculations.) Birthrate, x (number of births per 1000 pop.) Female life expectancy, y (in years) 41.3 15.6 52.1 32.0 47.0 49.7 27.2 19.8 13.3 24.6 36.4 49.4 Send data to calculator 66.8 76.7 60.5 62.2 58.9 53.4 71.2 72.8 73.9 74.3 66.2 63.0 xy 2758.84 1196.52 3152.05 1990.4 2768.3 2653.98 1936.64 1441.44 982.87 1827.78 2409.68 3112.2 Female life expectancy (in years) Figure 1 85- ^y 80- 75- 70- 65_ 60 55 1/46 15 20 25 30 35 40 45 50 55 60 Birthrate (number of births per 1000 pop.) What is the sample…

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The following table gives the lifetime in hours of 400 radio tubes of a certain make. Find the mean lifetime of the radio tubes. Number of tubes Lifetime (in hrs.) Less than 300 Number of tubes Lifetime (in hours) Less than 800 265 400 20 900 324 500 60 1,000 374 116 600 700 1,100 1,200 392 194 400