Answer:
-14a^2b-42ab^2+56abc
Step-by-step explanation:
You can use the FOIL method
multiply the first numbers
then inner
then outer
then last
Answer:
False
Step-by-step explanation:
Correlation is not causation.
It may mean that eating popsicles and buying sunglasses have a common cause: sunny days.
Answer:
0.94 cents
Step-by-step explanation:
If you multiply 0.67 with 141 you will see that you will end up with the same answer as above.
0.666 estimates to 0.67
Answer:
sometimes
hope it helps.
Answer:
sometimes
Step-by-step explanation:
OB. Rx) = (x + 1)2
OC. Rx) = -1(x - 1)
OD. Rx) = -1(x + 1)2
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Considering it's y-intercept and vertex, the equation of the parabola is given by:
The equation of a quadratic function, of vertex (h,k), is given by:
In which a is the leading coefficient.
In this problem, the vertex is (1,0), hence h = 1, k = 0 and:
The y-intercept is of 1, hence, when x = 0, y = 1, so:
Hence, the equation is:
More can be learned about the equation of a parabola at brainly.com/question/24737967
Answer:
A
Step-by-step explanation:
The equation of a parabola in vertex form is
y = a(x - h)² + k
where (h, k) are the coordinates of the vertex and a is a multiplier
Here (h, k) = (1, 0) , thus
y = a(x - 1)² + 0
To find a substitute the coordinates of the y- intercept (0, 1) into the equation
1 = a(- 1)² = a , thus
a = 1
y = (x - 1)² → A
Answer:
d. Decrease
Step-by-step explanation:
A Type II error is when we fail to reject a false null hypothesis. Higher values of α make it easier to reject the null hypothesis, so choosing higher values for α can reduce the probability of a Type II error.
The consequence here is that if the null hypothesis is true, increasing α makes it more likely that we commit a Type I error (rejecting a true null hypothesis).
So using lower values of α can increase the probability of a Type II error.
Raising the level of significance in a hypothesis test from .01 to .05 would decrease the probability of making a Type II error. This is because as we become more accepting of risk in making a Type I error, we simultaneously reduce the risk of making a Type II error.
The level of significance in a hypothesis test is the probability that we are willing to accept for incorrectly rejecting the null hypothesis or making a Type I error. If the level of significance is raised, there is a higher chance we incorrectly reject the null hypothesis, increasing the chances of a Type I error. However, this also has an effect on the probability of committing a Type II error, which is to incorrectly accept the null hypothesis.
Specifically, when the level of significance of a hypothesis test is raised from .01 to .05, the probability of a Type II error (option b) will decrease. The reason for this is that increasing the level of significance or alpha means we are more likely to reject the null hypothesis. As we are more accepting of risk in terms of making a Type I error, we are less likely to make a Type II error, as the two error types often move in opposite directions. Thus, the answer to your question is d. The probability of a Type II error will decrease if the significance level is raised from .01 to .05.
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Answer:
21
Step-by-step explanation:
Let the smallest of the numbers be N
The other two numbers (consecutive) would be written as (n + 2), (n + 4)
Expressing these as an equation gives : (n) + (n+2) + (n+4) = 69
opening the bracket and collecting like terms, we have:
n+n+n+2+4=69
3n + 6 = 69
3n = 69 - 6
3n = 63
Dividing both sides by 3 or making n the subject formular, we get:
n = 63/3
n = 21.
Note, the other numbers are: 21, 23, and 25
They are all odd numbers
Their sum equals to 69