Let denote H, - random event that demand for the new product is high, H, - that demand is average,and H, - that demand is low. Marketing specialist has calculated that P(H,)=0,3, P(H,)=0,5, andP(H,)=0,2. The product gains high evaluation, if it was highly evaluated by at least 70% ofconsumers. It is also known that in case of high demand probability for the product to gain highevaluation is 0,8; in case of average demand - 0,55, and in case of low demand - 0,3. Twentyconsumers of the product were interviewed recently, and fourteen highly evaluated it. What is theprobability that demand for the product will be high/average/low in case it was highly evaluated?

Answered: Image /qna-images/answer/74438ccf-f6b0-4f2f-9b57-effcda7f4dd8.jpg

Answered: Let denote H, - random event that…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

Two random variables X = (1,2) and Y= (-2,-1] are equiprobable and independent. Determine the correlation factor r(X,Y),
If P(A) = 0.5, P(B) = 0.4, and P(A^ B) = 0.25, then P(AUB) = 0.35 0.15 0.65 0.9
I have modeled adult worker's salaries based upon their work experience. After surveying 200 adults about their salary and years in the workforce, I have found the following model: y=12000+5000*x where y is the predicted salary and x is the years in the labor force. R^2 = 0.63. What is the correlation for this model? (correlation between salary and years in the labor force)? a. 0 b. 0.79 c. 0.63 d. 0.50 e. 1
Give a real-life situation/scenario where Random Variability (1 for Discrete, 1 for Continuous) is being applied/exhibited. /Like Real life situation for (1) passengers and (2) for patients
2 (a) Let Y be the random variable that counts the number of sixes which occur when a die is tossed 10 times. What type of random variable is Y? What is P (Y = 3), expected number of sixes,Var(Y )? (b) Let U be the random variable that counts the number of accidents that occur at an intersection in one week. What type of random variable is U? Suppose that, on average, 2 accidents occur per week. Find P(U = 2), E(U), and V ar(U). (c) Let X be the recorded body temperature of a healthy adult in degrees Fahrenheit. What type of rv is X? Estimate its mean and standard deviation, based on your knowledge of body temperatures.
None
The Poisson distribution gives the probability for the number of occurrences for a "rare" event. Now, let x be a random variable that represents the waiting time between rare events. Using some mathematics, it can be shown that x has an exponential distribution. Let x > 0 be a random variable and let β > 0 be a constant. Then y = 1 β e−x/β is a curve representing the exponential distribution. Areas under this curve give us exponential probabilities. If a and b are any numbers such that 0 < a < b, then using some extra mathematics, it can be shown that the area under the curve above the interval [a, b] is the following. P(a < x < b) = e−a/β − e−b/β Notice that by definition, x cannot be negative, so, P(x < 0) = 0. The random variable x is called an exponential random variable. Using some more mathematics, it can be shown that the mean and standard deviation of x are the following. μ = β and σ = β Note: The number e = 2.71828 is used throughout…
A researcher that wanted to estimate the expectation AY of a random variable Y got three independent observations, Y, Y, Y The researcher knows the value o, of the variance of Y and is considering the following estimators: Pi = 4) Yi + (+) ¥ Py = () Yn + (;) ¥½ + () Y½ in (}) Yi + (}) ¥z + (() %D Which of the following is correct? ONone of the above Ois an unbiased estimator of l and it has the smallest variance of the three estimators. Ois an unbiased estimator of µ and it has the smallest variance of the three estimators. O and i, are both unbiased estimators of fl and Var (ſîz) < Var (îì3). is an unbiased estimator of µ and it has the smallest variance of the three estimators.
True or False: For an exponentially distributed random variable, x, P(x) = 1/(b - a).
I have transportation data with a year variable, categorical and continuous variables. I tried to create a cross section by concatenating all the categorical variables together then regress on the continuous variables with revenue as my dependent variable using Pooled OLS. Unfortunately, i have serial correlation in my model and i am not able to remove the serial correlation. Alternatively, i was thinking of looking at just one year of data or treating the data as a single cross section, including year dummy variables and selecting specific categorical variables as additional dummy variables to determine the effect on revenue. Any issues with that approach or alternative recommendations? Also, its worth noting that i had to remove 15% of my data to ensure each cross section that i created had a year from 2011-2017 to allow me to run the proc panel in SAS.
If there is a perfect association between sexual attraction and accelerated heartbeat, then sex is unhealthy there is strong evidence that sexual attraction and accelerated heartbeat are causally related if there is no sexual attraction, the heartbeat never accelerates whenever the heartbeat accelerates, people become sexually attractive
I have a probability distribution consisting of (x, p(x)): (-3, 0.1), (-2, 0.2), (-1, 0.3), (0, 0.05). The probabilities obviously do not sum to 1. How do I find <x> (average), <x2> (the second moment), <sigmax2> (the variance)?

SEE MORE QUESTIONS

Recommended textbooks for you

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

SEE MORE TEXTBOOKS