(1 point) Consider the universal set U={1,2,3,4,5,6,7,8,9,10}, define the set A be the even numbers, the set B be the odd number
Sloan [31]
Answer:
a) AUC = {2,4,6,8,10}
b) BnC = {}
c) AnB = {}
d) B-C = B = {1,3,5,7,9}
Step-by-step explanation:
The set A is the even numbers, those that are divisible by two.
So A = {2,4,6,8,10}
B is the odd numbe.rs. An odd number is a number that is not divisible by two.
So B = {1,3,5,7,9}.
C = {4,5,6}, as the problem states
a) The union of sets is a set containing all elements that are in at least one of the sets. So the union of A and C is a set that contains all elements that are in at least one of A or C.
So AUC = {2,4,6,8,10}.
b) The intersection of two sets consists of all elements that in both sets. So, the intersection of B and C is the set that contains all elements that are in both B and C.
There are no elements that are in both B and C, so the intersection is an empty set
BnC = {}
c) Same explanation as b), there are no elements that are in both A and B, so another empty set.
AnB = {}
d) The difference of sets B and C consists of all elements that are in B and not in C. We already have in b) that BnC = {}, so:
B-C = B = {1,3,5,7,9}
Answer: C
Step-by-step explanation:
6 quarts equals 12 pints
8 quarts equals 2 gallons
48 fl oz equals 6 cups
Answer:
Step-by-step explanation:
Hello!
For me, the first step to any statistics exercise is to determine what is the variable of interest and it's distribution.
In this example the variable is:
X: height of a college student. (cm)
There is no information about the variable distribution. To estimate the population mean you need a variable with at least a normal distribution since the mean is a parameter of it.
The option you have is to apply the Central Limit Theorem.
The central limit theorem states that if you have a population with probability function f(X;μ,δ²) from which a random sample of size n is selected. Then the distribution of the sample mean tends to the normal distribution with mean μ and variance δ²/n when the sample size tends to infinity.
As a rule, a sample of size greater than or equal to 30 is considered sufficient to apply the theorem and use the approximation.
The sample size in this exercise is n=50 so we can apply the theorem and approximate the distribution of the sample mean to normal:
X[bar]~~N(μ;σ2/n)
Thanks to this approximation you can use an approximation of the standard normal to calculate the confidence interval:
98% CI
1 - α: 0.98
⇒α: 0.02
α/2: 0.01

X[bar] ± 
174.5 ± 
[172.22; 176.78]
With a confidence level of 98%, you'd expect that the true average height of college students will be contained in the interval [172.22; 176.78].
I hope it helps!