Create a diagram showing the distributions in question 3 and describing the relationships between them. 3.For each distributio
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1.Create a diagram showing the distributions in question 3 and describing the relationships between them.
3.For each distribution show (algebraically derive) the method of moments estimates of parameters of:
a.Uniform distribution
b.Gamma distribution
c.Beta distribution
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- 6. ?Question 4 The ten year extreme wave height (H) at a site of interest for offshore drilling and extraction can be assumed to floow Rayleigh distribution with a mean wave height of 16 ft. ( mean wave height = 2.5 x o). Determine the following: • Probability of a wave height greater than 24 feet. • Probability of a wave height less than or equal to 18 feet. • Probability of seeing a wave less than or equal to 24 feet, but greater than 18 feet. • What is the one in 50000 wave height? (i.e. the wave height that has a probability of 0.002% of being exceeded.)#15
- ) Question 1 Which describes a normal distribution with mean μ and variance o²? O Its curve intersects the horizontal axis at two points. O Increasing u shifts the curve to the right. O Its mode and median are both greater than μ. O Increasing o makes the curve thinner and sharper.This Question: 1 pt 7 of 50 (0 complete) v Consider the discrete data in the table below. a) Construct a frequency distribution. a) Construct a frequency distribution. Data Value Frequency b) Construct a relative frequency distribution. c) Construct a cumulative relative frequency distribution. 1 2 1 4. 1 3 3 3 2 4 4 3 3 2 4 1 2 b) Construct a relative frequency distribution. 1 3 3 Relative Data Value Frequency 1 2 3 4 (Round to the nearest thousandth as needed.) OODODquestion 8
- Complete the given relative frequency distribution and compute the stated relative frequencies. (a) P({1, 3, 5}) Step 1 Outcome 1 Rel. Frequency 0.1 0.2 (b) P(E) where E = {1, 2, 3} (a) P({1, 3, 5}) 2 Outcome 1 0.1 2 4 We are given the incomplete relative frequency distribution. 3 0.1 5 4 5 Rel. Frequency 0.1 0.2 0.1 0.1 The missing table value is the relative frequency value corresponding to the outcome 0.5 X 5Q.5 The following distribution shows the drying times in hours of a certain brand of latex paint. Draw its frequency curve and comment on it about the trend of drying times. Drying Times (Hours) Frequency 2.0-2.4 2.5-2.9 3.0-3.4 3.5-3.9 4.0-4.4 4.5-4.9 12 15 20 25 18 10Question Z Consider the following incomplete grouped frequency distribution. Classes (Rand) Frequency Cumulative frequency 24 8.00 < 12.00 24 12.00 < 16.00 X Y 16.00 < 20.00 46 102 20.00 < 24.00 18 120 TOTALS 120 The midpoint m of the third class is Select one: А. 14.0 В. 18.0 С. 10.0 D. 22.0
- d. Population size e. Shape of the distribution f. Is this variable discrete or 40-49.9 15 50-59.9 10 60-69.9 continuous? g. Make a histogram or a bar chart (as appropriate) for this data. 70-79.9 1 2. A researcher visited 29 randomly selected Starbucks locations and recorded the number of cappuccinos sold at each coffee shop on March 22. He summarized the data in the following frequency distribution table: For this scenario, identify the following: 1. Variable 2. Individual (Subject) 3. Sample 4. Sample size 5. Class (bin) width 6. Is the variable discrete or Variable Frequency 5-9 10-14 15-19 8. 20-24 10 continuous? 25-29 4 7. How many Starbucks locations sold at least 10 cappuccinos? 8. What percent of Starbucks locations sold at least 10 cappuccinos? 3. This table presents the price distribution of shoe styles offered by an online outlet. Variable FreguencyY 2.RstudioThis cumulative review problem uses material from Chapters 3, 5, and 10. Recall that the Poisson distribution deals with rare events. Death from the kick of a horse is a rare event, even in the Prussian army. The following data are a classic example of a Poisson application to rare events. The data represent the number of deaths from the kick of a horse per army corps per year for 10 Prussian army corps over a period of time. Let x represent the number of deaths and f the frequency of x deaths. x 0 1 2 3 or more f 111 61 24 4 (a) First, we fit the data to a Poisson distribution.The Poission distribution states P(x) = e−λλx x! , where λ ≈ x (sample mean of x values). From our study of weighted averages, we get the following. x = Σxf Σf Verify that x = 0.605. Hint: For the category 3 or more, use 3. x = (b) Now we have P(x) = e−0.605(0.605)x x! for x = 0, 1, 2, 3 . Find P(0), P(1), P(2), and P(3 ≤ x). Round to three places…