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3 years ago

6

The unit price is $2.50

2 answers:

makkiz [27]3 years ago

8 0

Answer:

The answer is 3.

Step-by-step explanation:

If you divide 7.50 by 2.50, you get 3. Hope this helps! And have an amazing day!

Deffense [45]3 years ago

7 0

The answer is 3. The weight of the package is 3 because if you divide 7.50 and 2.50 you get 3..

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The manufacturer of an electronic device claims that the probability of the device failing during the warranty period is 0.005.

Zielflug [23.3K]

Answer:

The value is $P(X \ge 15) = 0.5$

Step-by-step explanation:

From the question we are told that

The probability of the device failing during the warranty period is $p = 0.005$

The sample size is $n = 3000$

The random variable considered is x = 15

Generally this is distribution is binomial given the fact that there is only two out comes hence

X which is a variable representing a randomly selected selected electronic follows a binomial distribution i.e

$X \~ \ B(n , p)$

Now the mean is mathematically evaluated as

$\mu = n * p$

=> $\mu = 3000 * 0.005$

=> $\mu =15$

The standard deviation is mathematically represented as

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

=> $\sigma = \sqrt{3000 * 0.005 * (1 - 0.005 )}$

=> $\sigma = 3.86$

Now given that n is very large, then it mean that we can successfully apply normal approximation on this binomial distribution

So

$P(X \ge 15) = P( \frac{X - \mu}{\sigma } \ge \frac{x - \mu}{\sigma } )$

Now applying Continuity Correction we have

$P(X \ge (15-0.5)) = P( \frac{X - \mu}{\sigma } > \frac{(15 -0.5) - 15}{3.86 } )$

Generally $\frac{X - \mu}{\sigma } = Z (The \ standardized \ value \ of \ X)$

$P(X \ge (15-0.5)) = P(Z >-0.130 )$

From the z-table

$P(Z >-0.130 ) =0.5$

Thus

$P(X \ge 15) = 0.5$

7 0

4 years ago

PLEASE EXPLAIN Find the area and perimeter of the rectangle whose sides are lengths 2x + 3 and 4x

SIZIF [17.4K]

Area = 4x(2x + 3) = 8x2 + 12x

Perimeter = 2(2x + 3 + 4x) = 12x + 6

4 0

3 years ago

Which bracelet has the highest portion of gold? Bracelet: ______

Tanya [424]

Answer:

B

Step-by-step explanation:

6 0

3 years ago

An experiment was conducted to observe the effect of an increase in temperature on the potency of an antibiotic. Three 1-ounce p

ludmilkaskok [199]

Answer:

a) $y=-0.317 x +46.02$

b) Figure attached

c) $S^2=\hat \sigma^2=MSE=\frac{190.33}{10}=19.03$

Step-by-step explanation:

We assume that th data is this one:

x: 30, 30, 30, 50, 50, 50, 70,70, 70,90,90,90

y: 38, 43, 29, 32, 26, 33, 19, 27, 23, 14, 19, 21.

a) Find the least-squares line appropriate for this data.

For this case we need to calculate the slope with the following formula:

$m=\frac{S_{xy}}{S_{xx}}$

Where:

$S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}$

$S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}$

So we can find the sums like this:

$\sum_{i=1}^n x_i = 30+30+30+50+50+50+70+70+70+90+90+90=720$

$\sum_{i=1}^n y_i =38+43+29+32+26+33+19+27+23+14+19+21=324$

$\sum_{i=1}^n x^2_i =30^2+30^2+30^2+50^2+50^2+50^2+70^2+70^2+70^2+90^2+90^2+90^2=49200$

$\sum_{i=1}^n y^2_i =38^2+43^2+29^2+32^2+26^2+33^2+19^2+27^2+23^2+14^2+19^2+21^2=9540$

$\sum_{i=1}^n x_i y_i =30*38+30*43+30*29+50*32+50*26+50*33+70*19+70*27+70*23+90*14+90*19+90*21=17540$

With these we can find the sums:

$S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=49200-\frac{720^2}{12}=6000$

$S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}=17540-\frac{720*324}{12}{12}=-1900$

And the slope would be:

$m=-\frac{1900}{6000}=-0.317$

Nowe we can find the means for x and y like this:

$\bar x= \frac{\sum x_i}{n}=\frac{720}{12}=60$

$\bar y= \frac{\sum y_i}{n}=\frac{324}{12}=27$

And we can find the intercept using this:

$b=\bar y -m \bar x=27-(-0.317*60)=46.02$

So the line would be given by:

$y=-0.317 x +46.02$

b) Plot the points and graph the line as a check on your calculations.

For this case we can use excel and we got the figure attached as the result.

c) Calculate S^2

In oder to calculate S^2 we need to calculate the MSE, or the mean square error. And is given by this formula:

$MSE=\frac{SSE}{df_{E}}$

The degred of freedom for the error are given by:

$df_{E}=n-2=12-2=10$

We can calculate:

$S_{y}=\sum_{i=1}^n y^2_i -\frac{(\sum_{i=1}^n y_i)^2}{n}=9540-\frac{324^2}{12}=792$

And now we can calculate the sum of squares for the regression given by:

$SSR=\frac{S^2_{xy}}{S_{xx}}=\frac{(-1900)^2}{6000}=601.67$

We have that SST= SSR+SSE, and then SSE=SST-SSR= 792-601.67=190.33[/tex]

So then :

$S^2=\hat \sigma^2=MSE=\frac{190.33}{10}=19.03$

5 0

3 years ago

I neeeddd help pleaase

Norma-Jean [14]

I got 65 for my answer. Hope that helps!

7 0

3 years ago