1. Give one example of a transportation decision that could be measured with a continuous variable.
2. Give one example of a transportation decision that could be measured with a discrete variable.
1) A continuous variable is that variables which can take all the values between two real numbers. There are infinite possible numbers for a continuous variable. In a transportation problem, if the rate is charged as per weight, then the weight is a continuous variable. Suppose maximum load a truck can take is 10 tons. Then, the weight can be any value between 0 and 10 tons and there are infinite possibilities.
2)
A discrete variable is that variable which can only take a value from a particular set of values. In transportation case, if the rate is charged per unit transferred, then number of units is a discrete variable. Units can only be whole numbers. Suppose maximum units is 100. It can take all whole number from 0 to 100 and there are 101 possibilities.
1. Give one example of a transportation decision that could be measured with a continuous variable....
Give an example of a discrete
or continuous random variable X (by giving the p.m.f. or p.d.f.)
whose cumulative distribution function F(x) satisfies F(n)=1-1/n!
Thank you very much!
Exercise 3.40. Give an example of a discrete or continuous random variable X p.d.f.) whose the cumulative distribution function F(x) (by giving the p.m.f satisfies F(n)1 - i for each positive integer n or
Is the quantitative variable discrete or continuous? The number of customers served in one day at the drive through in a local bank. The variable is discrete because it is not countable The variable is continuous because it is measured and not countable. The variable is continuous because it is not measured. The variable is discrete because it is countable
Answer the following: a) Describe the difference between a discrete and a continuous random variable. Give an example of each. b) Describe probability density function c) Differentiate between retrospective and observational studies d) What is the significance of the Central Limit Theorem in statistics?
Could you give me an daily life example of transformation of random variables both discrete and continuous?
1. Identify a dependent variable and give examples of how it could be measured at each of the levels of measurement: nominal, ordinal, and interval/ratio level. Think about research questions that may be addressed using the following statistical tests: (Post one question for each test) * ANOVA * T-test State how the DV is measured. Please include your reference in APA format 2. Pls Search American Hospital Association website http://www.aha.org/aha/about/index. Click on issues and select one issue to explore. Report on...
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a. Is the transportation model an example of decision making under certainty or decision making under uncertainty? Why? a. What is a balanced transportation model? Describe the approach you would use to solve an unbalanced model? 2.What is the minimal-spanning tree model? Give several examples of problems that can be solved using this type of model. 3.What is the maximal-flow model? What types of problems can be solved using this type of model? 4.Describe a problem that...
Give one example of a behavior that is conducive for continuous measurement procedures. Then, give one example of a behavior that is conducive for sampling procedures. Explain how each is the most appropriate for facilitating the collection of accurate and reliable data for the target behavior.
Determine whether the following value is a continuous random variable, discrete random variable, or not a random variable. a. The number of textbook authors now eating a mealnumber of textbook authors now eating a meal b. The usual mode of transportation of people in City Upper Ausual mode of transportation of people in City A c. The number of statistics students now doing their homeworknumber of statistics students now doing their homework d. The number of runs scored during a...
Give an example(s) of non-monetary information that could be measured by a company that will help a company's performance.
1. A Binomial random variable is an example of a, a continuous random variable b. a discrete random variable. c. a Binomial random variable is neither continuous nor discrete d. a Binomial random variable can be both continuous and discrete. Consider the following probability distribution where random variable X denotes the number of cups of coffee a random individual drinks in the morning P(x) 0.350 .400 .14 0.07 0.03 0.01 pe a. Compute the probability that a random individual drinks...