Do you have a picture of the graph, but if there is a dilation there will be a small plane and a big on on the same graph and one will have a ‘ by the point letter representing it’s the 2 image
Answer:
45 ft^2.
Step-by-step explanation:
Area = area of the square + 2 * area of one triangle
= 5^2 + 2 * 1/2 * 5 * 4
= 25 + 20
= 45 fT^2.
Answer:
The answer is below
Step-by-step explanation:
Shoppers at a mall have a mean weight of 70 kg with a standard deviation of 10 kg. An elevator at the mall holds a maximum of 6 people, and safety engineers are curious about the average weight of shoppers on a full elevator. Suppose that we take random samples of 6 shoppers and calculate the mean weight x ˉ on top of the shoppers in each sample.
Solution:
Let variable x represent the weight of a shopper at the mall.
Assuming this variable has a normal distribution with mean μ= 70kg and standard deviation σ = 10kg.
There are random samples of 6 shoppers. That is sample size (n) = 6
The mean of the sample (μₓ) is the same as the mean of the population (μ), hence:
μₓ = μ = 70 kg
The standard deviation of the sample (σₓ) is equal to the standard deviation of the population (σ) divided by the square root of the sample size (n).. Hence:
σₓ = σ / √n = 10 / √6 = 4.08 kg
Answer:
a) 
b) 
Step-by-step explanation:
Previous concepts
The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".
Solution to the problem
Part a
Let X the random variable "number of people math phobicmath phobic" , on this case we now that the distribution of the random variable is:
The probability mass function for the Binomial distribution is given as:
Where (nCx) means combinatory and it's given by this formula:
And we want this probability:
If we use the probability mass function we got:
Part b
For this case we want this probability:
We can find first this probability
