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Ostrovityanka [42]
3 years ago
9

47 ounces to 54 ounces

Mathematics
1 answer:
Oksanka [162]3 years ago
3 0
<span>From 47 ounces to 54 ounces is: 14.9% increase.    </span>
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Please help. The question is in the pictures. Thanks :)
mylen [45]

Answer:

Scalene

Step-by-step explanation:

Scalene triangles always have unequal side lengths. Thia triangle has unequal side lengths, therefore it is considered scalene.

8 0
3 years ago
Which Natural Numbers are not Integers?
Genrish500 [490]

Answer:

Step-by-step explanation:

fraction are not integers

6 0
3 years ago
Can you fill in the blanks. Thx
maria [59]

Answer:

Answer is below

Step-by-step explanation:

Download docx
4 0
3 years ago
A sample with a mean of m = 40 and a variance of s2 = 20 has an estimated standard error of 1 point. how many scores are in the
tamaranim1 [39]

The correct option is 20.

The score found for the sample is 20.

<h3>What is Standard error?</h3>

A standard error is a statistic that is applied to test the distribution of data. This metric is comparable to standard deviation. We can calculate the standard error if we know the sample size & standard deviation. It assesses the mean's precision.

Now, according to the question;

Sample mean; \bar{x}=40

Sample variance; s^{2}=20

Thus, s=\sqrt{20}=4.47

Standard error SE = 1

The amount of scores with in sample must be determined here.

The standard error formula is as follows:

S E=\frac{s}{\sqrt{n}}

We might rearrange the formula as follows:

\begin{aligned}\sqrt{n} &=\frac{s}{S E} \\n &=\left(\frac{s}{S E}\right)^{2}\end{aligned}

Substituting the values;

\begin{aligned}&n=\left(\frac{4.47}{1}\right)^{2} \\&n=19.98\end{aligned}

The sample's number of scores n = 19.98 = 20 (round up)

Therefore, the scores are in the sample is 20.

To know more about the Standard error, here

brainly.com/question/14467769

#SPJ4

3 0
2 years ago
(4.1.4) Let X and Y be Bernoulli random variables. Let Z = X + Y. a. Show that if X and Y cannot both be equal to 1, then Z is a
Fynjy0 [20]

Step-by-step explanation:

Given that,

a)

X ~ Bernoulli (p_x) and Y ~ Bernoulli (y_x)

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,

p_z = P(X=1 or Y=1)\\

p_z = P(X=1)+P(Y=1)-P(=1 and Y =1)

p_z = P(x=1)+P(Y=1)\\\\p_z=p_x+p_y

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

7 0
3 years ago
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