Answer:
Answers explained below
Step-by-step explanation:
(a) If there is high bias and high variability, the numbers will not be anywhere near the 42 percent value. If I wrote down 10 numbers and they were all completely different from 42, I would know that I have high bias and high variability.
(b) If a certain number of polls have just about the same average, but are nowhere near 42 percent, they have high bias and low variability. For example, 20 percent, but its far from 42 percent.
(c) If there is low bias and high variability, if you list the polls they will have an average around 42 percent. If you average the polls, you'll get 42 percent low bias. The high variability might be 20, 72% 42% 63% 10%
(d) If there is low bias and low variability, all of the polls will be close to 42 percent.
If the discriminant is negative no real solution exists.
If the discriminant is equal to 0 only one real solution exists.
If the discriminant is positive 2 real solutions exist.
The discriminant:
D = b² - 4 a c
1 ) - 7 x² + 6 x + 3 = 0
D = 6² - 4 · ( - 7 ) · 3 = 36 + 84 = 120 > 0
Answer: b) two solutions
2 ) - 8 x² - 8 x - 2 = 0
D = ( - 8 )² - 4 · ( - 8 ) · ( - 2 ) = 64 - 64 = 0
Answer: a ) one solution
Answer:
rewrite what as the unit rate?
Step-by-step explanation:
What is the question
Step-by-step explanation:
Given that,
a)
X ~ Bernoulli 
and Y ~ Bernoulli 
X + Y = Z
The possible value for Z are Z = 0 when X = 0 and Y = 0
and Z = 1 when X = 0 and Y = 1 or when X = 1 and Y = 0
If X and Y can not be both equal to 1 , then the probability mass function of the random variable Z takes on the value of 0 for any value of Z other than 0 and 1,
Therefore Z is a Bernoulli random variable
b)
If X and Y can not be both equal to 1
then,
or 
and 
c)
If both X = 1 and Y = 1 then Z = 2
The possible values of the random variable Z are 0, 1 and 2.
since a Bernoulli variable should be take on only values 0 and 1 the random variable Z does not have Bernoulli distribution
Memorize the definition of standard deviation: the sd is the square root of the average of the squared deviations of the mean. Wow. Let's do it.
Step 1. First we need the mean. That's easy. Add them up and divide by the count. Check if you get 16.88/5 = 2.81333.
Step 2. Now we're going to subtract this from each of the values, and square the result. Don't worry about negative signs, the squaring will get rid of those. Example for the first number:
(1 - 2.813)^2 = 3.29
The list of numbers I get is (rounded, in reality round as little as possible):
3.29, 2.60, 1.41, 2.35, 1.66, 6.18
Step 3: Add them all up. I get 17.49.
Step 4: Divide by the count of numbers. 17.49/6 = 2.91
Step 5: Take the square root from this result. SQRT(2.91) = 1.707305
TIP: Use excel to do all these steps, then run the set of numbers through Excel's built-in sd function (called STDEV.P) and see that you get the same result!
