Answer with Step-by-step explanation:
We are given that A and B are two countable sets
We have to show that if A and B are countable then 
is countable.
Countable means finite set or countably infinite.
Case 1: If A and B are two finite sets
Suppose A={1} and B={2}
={1,2}=Finite=Countable
Hence, is countable.
Case 2: If A finite and B is countably infinite
Suppose, A={1,2,3}
B=N={1,2,3,...}
Then, ={1,2,3,....}=N
Hence, is countable.
Case 3:If A is countably infinite and B is finite set.
Suppose , A=Z={..,-2,-1,0,1,2,....}
B={-2,-3}
=Z=Countable
Hence, countable.
Case 4:If A and B are both countably infinite sets.
Suppose A=N and B=Z
Then,=
=Z
Hence, is countable.
Therefore, if A and B are countable sets, then is also countable.
Graph b
The domain is (-inf,inf)
The range is [0, inf)
Hope this helps!
Answer:
Step-by-step explanation:
We have the polynomial x^2 + 18x + 81 and are being asked to factor this into two binomials.
A rule that I follow is what two numbers multiplied make c (in this case 81) and when added make b (in this case is 18).
So what two numbers when :
A. Multiplied make 81
B. Added make 18
This would be 9.
Now that we have the answer, we can put it into binomials.
(x + 9)(x + 9)
Since these are the same, we can combine it and make it into one.
If all the cheese slices have same mass, say m grams
and mass of 3 cheese slices is 27
so,
m+m+m=27
3m=27
or m=27/3
m=9
thus
mass of one cheese slice is 9 grams
Answer:
a) 
b) From the central limit theorem we know that the distribution for the sample mean 
is given by:
c) 
Step-by-step explanation:
Let X the random variable the represent the scores for the test analyzed. We know that:
And we select a sample size of 64.
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Part a
For this case the mean and standard error for the sample mean would be given by:
Part b
From the central limit theorem we know that the distribution for the sample mean is given by:
Part c
For this case we want this probability:
And we can use the z score defined as:
And using this we got:
And using a calculator, excel or the normal standard table we have that:
