PLEASE HELP ME! ANSWER CORRECT AND GET BRAINLIEST*! (If more than one answer)

Find all the zeros of the equation 12x^2-64=-x^4

Natalija [7]

Answer: all the zeroes of the above equation will be

(x-4)(x+4)(x-2)(x+2)

Step-by-step explanation:

Since we have given that

$12x^2-64=-x^4\\\\x^4+12x^2-64=0$

We need to find the zeroes of the above equation.

So, we will use "Split the middle terms" :

$x^4+12x^2-64=0\\\\x^4+16x^2-4x^2-64=0\\\\x^2(x^2-16)-4(x^2-16)=0\\\\(x^2-4)(x^2-16)=0\\\\x^2-4=0\ or\ x^2-16=0\\\\\text{ "Using }a^2-b^2=(a+b)(a-b)"\\\\x^2-4=x^2-2^2=(x-2)(x+2)\\\\x^2-16=x^2-4^2=(x+4)(x-4)$

So, all the zeroes of the above equation will be

(x-4)(x+4)(x-2)(x+2)

7 0

2 years ago

3.30 Survey response rate. Pew Research reported in 2012 that the typical response rate to their surveys is only 9%. If for a pa

Artist 52 [7]

Answer:

0% probability that at least 1,500 will agree to respond

Step-by-step explanation:

I am going to use the binomial approximation to the normal to solve this question.

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

In this problem, we have that:

$n = 15000, p = 0.09$

So

$\mu = E(X) = np = 15000*0.09 = 1350$

$\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{15000*0.09*0.91} = 35.05$

What is the probability that at least 1,500 will agree to respond

This is 1 subtracted by the pvalue of Z when X = 1500-1 = 1499. So

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

$Z = \frac{1499 - 1350}{35.05}$

$Z = 4.25$

$Z = 4.25$ has a pvalue of 1.

1 - 1 = 0

0% probability that at least 1,500 will agree to respond

6 0

2 years ago

Herbert plans to use the earnings from his lemonade stand according to the table above, for the first month of operations. If he

FinnZ [79.3K]

Table is attached below

From the table we can see that the Lemon cost is equal to 35% of the expenses

Let the expense be x, Lemons cost is 70

Lemon cost = 35% * x

70 = 35% * x ( 35% = $\frac{35}{100}$ = 0.35)

70 = 0.35 * x

x = $\frac{70}{0.35}$

x= 200, Expense = $200

Given : Profit percentage is 15%= $\frac{15}{100}$ = 0.15

Profit = profit percentage * Expense

Profit = 0.15 * 200 = 30

So profit = $30

5 0

2 years ago

Read 2 more answers

you plan to buy a bicycle that will cost at least 180. you have saved 38 and your parents have given you 50. how much more money

shutvik [7]

Answer:

$92

Step-by-step explanation:

add what you saved and the parents gave you
subtract that by 180
$92

4 0

2 years ago

Anna set up a lemonade stand on her block over the summer. She recorded each day’s high temperature and the number of cups of le

Alexxx [7]

Answer:

Residual = -2

The negative residual value indicates that the data point lies below the regression line.

Step-by-step explanation:

We are given a linear regression model that relates daily high temperature, in degrees Fahrenheit and number of lemonade cups sold.

$y = -34+ \frac{3}{5} x$

Where y is the number of cups sold and x is the daily temperature in Fahrenheit.

Residual value:

A residual value basically shows the position of a data point with respect to the regression line.

A residual value of 0 is desired which means that the regression line best fits the data.

The Residual value is calculated by

Residual = Observed value - Predicted value

The predicted value of number of lemonade cups is obtained as

$y = -34+ \frac{3}{5} (95)\\\\y = -34+ 3 (19)\\\\y = -34+ 57\\\\y = 23$

So the predicted value of number of lemonade cups is 23 and the observed value is 21 so the residual value is

Residual = Observed value - Predicted value

Residual = 21 - 23

Residual = -2

The negative residual value indicates that the data point lies below the regression line.

7 0

2 years ago