Answer:
there is no question
Step-by-step explanation:
It looks like the owner plays dirty, meaning he uses a trick of some kind to somehow influence the outcome in such a way, that it's outcome is no longer random.
By influencing the outcome, the owner can obtain an advantage over the playeers who are not aware of the trick or skill involved.
This is unfair and can be considered "dirty". This game is 'fixed'.
2006 and later
First, plug in 60 for y. Then subtract 17.1 from both sides, and you get 42.9 = 14.3x, from which you divide 14.3 from both sides to isolate x. Since x = 3, the businesses will be spending less than or equal to $60 billion up to 3 years after 2002. The fourth year, which is 2006, will be greater than $60 billion
Answer:
a) Poisson distribution
use a Poisson distribution model when events happen at a constant rate over time or space.
Step-by-step explanation:
<u> Poisson distribution</u>
- Counts based on events in disjoint intervals of time or space produce a Poisson random variable.
- A Poisson random variable has one parameter, its mean λ
- The Poisson model uses a Poisson random variable to describe counts in data.
use a Poisson distribution model when events happen at a constant rate over time or space.
<u>Hyper geometric probability distribution</u>:-
The Hyper geometric probability distribution is a discrete probability distribution that describes the probability of successes (random draws for which the object drawn has a specified feature) in draws without replacement, from a finite population of size that contains exactly objects with that feature where in each draw is either a success or failure.
This is more than geometric function so it is called the <u>Hyper geometric probability distribution </u>
<u></u>
<u>Binomial distribution</u>
- The number of successes in 'n' Bernoulli trials produces a <u>Binomial distribution </u>. The parameters are size 'n' success 'p' and failure 'q'
- The binomial model uses a binomial random variable to describe counts of success observed for a real phenomenon.
Finally use a Binomial distribution when you recognize distinct Bernoulli trials.
<u>Normal distribution</u>:-
- <u>normal distribution is a continuous distribution in which the variate can take all values within a range.</u>
- Examples of continuous distribution are the heights of persons ,the speed of a vehicle., and so on
- Associate normal models with bell shaped distribution of data and the empirical rule.
- connect <u>Normal distribution</u> to sums of like sized effects with central limit theorem
- use histograms and normal quantile plots to judge whether the data match the assumptions of a normal model.
<u>Conclusion</u>:-
Given data use a Poisson distribution model when events happen at a constant rate over time or space.
The coefficient of 2xy3 is 2
Answer:
I wanna say b
Step-by-step explanation:
I'm gonna say b because u would think since they've paid $13, and it sells for $22, u would add that on the price, which in my opinion would be x + 13 = 22