The population of Clayton is

Whitney kicks a football off the ground. The height, h , in feet, of the football above the ground after t seconds is given by h

malfutka [58]

Answer:

after 4seconds

Step-by-step explanation:

Given the height, h , in feet, of the football above the ground after t seconds expressed by h ( t ) = − 8 t^2 + 32 t, the height of the ball on the ground is 0feet.

Substitute h(t) = 0 into the expression and calculate t;

h ( t ) = − 8 t^2 + 32 t

0 = − 8 t^2 + 32 t

8t² = 32t

8t = 32

Divide both sides by 8

8t/8 = 32/8

t = 4s

Hence the football hits the ground after 4seconds

5 0

3 years ago

13(6x – 5) – x = 13 – 2(x + 1

elena-s [515]

Answer:

Step-by-step explanation:

$13(6x-5)-x=13-2(x+1)\\78x-65-x=13-2x-2\\77x-65=11-2x\\77x+2x=11+65\\x=76/79\\x=0.9620$

6 0

3 years ago

When do you carry the high number in vertical multiplication

tangare [24]

When it is greater than 9.

Example

15
x 5
——-

5x5 is 25, so you would leave 5 and carry the 2

2
15
x. 5
——-
5

3 0

3 years ago

Consider the probability that no less than 96 out of 145 people will not get the flu this winter. Assume the probability that a

dsp73

Answer:

0.1324 = 13.24% probability that no less than 96 out of 145 people will not get the flu this winter.

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .