the total amount of air that the lung can hold; normally it is 6 litters for adult male and 4.2 litters for an adult female. The vital capacity (VC) measures the maximum amount of air that can be inhaled or exhaled during a respiratory cycle. The Residual Volume (RV) is the amount of gas remaining the lungs after a maximal expiration; normally it takes up 20% of the total lung capacity. VC + RC = TLC. The Inspiratory Reserved Capacity (IRC) is the amount of air that can be inhaled after the end of
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capacities. Results from this particular experiment may deviate from the predicted values obtained using the Goldman and Becklake equations for Pulmonary function if the individual tested has a habit of smoking which could lead to a drop in functional residual capacity. The natural recoil of the lung is also evident in figure 1. During natural inspiration‚ the volume of air increases in an exponential manner until it reaches the inspiratory reserve volume. The shape of the plot proves that muscular action
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Experimental Errors and Uncertainty No physical quantity can be measured with perfect certainty; there are always errors in any measurement. This means that if we measure some quantity and‚ then‚ repeat the measurement‚ we will almost certainly measure a different value the second time. How‚ then‚ can we know the “true” value of a physical quantity? The short answer is that we can’t. However‚ as we take greater care in our measurements and apply ever more refined experimental methods‚ we can reduce
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closely. In the past‚ 15% of the parts produced would be defective. The manager wants to determine the proportion of parts currently produced that are defective. What is the minimum sample size he should take so that at 95% confidence the margin of error will not be more than 0.08? a. 77 b. 102 c. 139 d. 185 2. A department store is considering a new credit policy to try to reduce the number of customers defaulting on payments. A suggestion is made to discontinue credit to any customer who
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STUDENT PERFORMANCE DETERMINANTS IN A BUSINESS STATISTICS COURSE AT A LARGE URBAN INSTITUTION CIS 3300 November 30‚ 2012 INTRODUCTION This research paper discusses the effects of several different factors on a student’s success in a Business Statistics course. The different variables include areas related to the student’s academic factors as well as factors related to the student’s personal life. The academic related variables are: course of study‚ study hours per week‚ semester credit
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(Wilensky & Lebeaux‚ 1965) spoke of two concepts of social welfare services and they are the residual social welfare and the institutional social welfare. These concepts are geared towards the path of preventive or responsive upkeep to persons in society. Residual Social Welfare comes into effect when all other resources such as support from family‚ religious aspects and the market economy have been depleted before assistance is given. This approach is only for a short period until such person
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Statistics Quiz 2 Prof. Fierimonte Name Shana Hicks .5 MULTIPLE CHOICE Find the indicated probability. | 1) The table below describes the smoking habits of a group of asthma sufferers. 1) | | Light | Heavy | | Non-smoker | Smoker | Smoker | Total | Men | 431 | 44 | 41 | 516 | Women | 378 | 37 | 48 | 463 | Total | 809 | 81 | 89 | 979 | If two different people are randomly selected from the 979 subjects‚ find the probability
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Major Statistics Assignment Mary Grace Rivero 050853639 CNUR860-011 Vaska Micevski Friday‚ March 30‚ 2012 Major Statistics Assignment This major statistics assignment will finally pull together everything that was learned in this course. The application of all content within this course will be incorporated to three different research scenarios. Within each scenario‚ hypothesis testing will be done‚ followed by a discussion of relevant descriptive statistics and finally‚ a discussion
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Millar Biology statistics made simple using Excel Biology statistics made simple using Excel Neil Millar Spreadsheet programs such as Microsoft Excel can transform the use of statistics in A-level science Statistics is an area that most A-level biology students (and their teachers!) find difficult. The formulae are often complicated‚ the calculations tedious‚ degrees of freedom mysterious‚ and probability tables confusing. But in fact students need no longer grapple with any of these.
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8047‚ mean square error is 76.87. The second predictor entered into the stepwise model is X1. The estimated intercept is -127.596‚ the estimated slope for X1 is 0.3485 and the slope for X3 is 1.8232. The R2-value is 0.933 and the mean square error is 27.575. The final predictor entered is X4. The estimated intercept is -124.20‚ the estimated slope for X4 is 0.5174‚ the slope for X1 adjusts to 0.2963 and the slope for X3 adjusts to 1.357. The R2-value is 0.9615 and the mean square error is 16.581. Predictor
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