Answer: Maggie is 7 years old.
Step-by-step explanation:
Maggie = x years old
Maggie’s brother = 4x - 3 years old
x + 4x - 3 = 32
5x -3 = 32
5x = 35
x = 7
In the above question 13m=156 we are dividing both sides by 13 so that m=12 .As 
According to Division property of Equality: If you divide one side of an equation by a number, you also must divide the other side by the same number so that your equation stays the same.
The property Division Property of Equality is justified .
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:
we cant see the data
Step-by-step explanation:
I believe it’s -6 square root of 2 + 3 square root of 4 + 6 square root of 5
