Answer:
4 1/12
Step-by-step explanation:
1 1/3 = 1 4/12
2 3/4 = 2 9/12
1 4/12 + 2 9/12 = 3 13/12 or <u><em>4 1/12</em></u>
I hope this helps!
-TheBusinessMan
The probability is 1/5, 1:4(favorable), or 4:1 (unfavorable)
Hope this helps
Answer:
$500
Step-by-step explanation:
substitute the values for X & S in the equation from part A:
y=20x + 0.15s
x=($20x25) + (0.15x$0)
= $500
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.
Answer:
B. y = -x + 2
Step-by-step explanation:
Now, the standard slope formula is y = mx + b, where m is the slope and b is the y intersect. From the graph pictured, we know that it has a slope of 1 since it goes up one point and to the right one point. So, I know the equation of this line is y = x + 2. Now, all that is left is to find this equation with a -x, which indicates that it is a -1 slope. Since option B has the formula y = -x + 2, that is the correct answer.