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andre [41]
4 years ago
9

What does W equal? -22-3w-5w=0

Mathematics
1 answer:
DerKrebs [107]4 years ago
3 0

In the International System of Units (SI), the unit of power is the watt (W), which is equal to one joule per second.

SI unit: watt (W)

In SI base units: kg⋅m2⋅s−3

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There were 8 socks of white, green and blue shuffled in a draw. The probability of selecting a white sock is 1/4. What is the pr
katrin2010 [14]

Answer:

P(select green sock) = 1/8

Step-by-step explanation:

If the probability of selecting a white sock is 1/4, then we know there are 2 white socks:  1/4 has the same value as 2 out of 8.

Similarly, we can determine the number of yellow socks:  5/8 is equivalent to 5 out of 8.

Thus, 2 socks are white; 5 are yellow; and the last (the 8th) sock is green.

P(select green sock) = 1/8

8 0
3 years ago
-3/7*(-8)= plzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz
Sindrei [870]

Answer:

3.42857143

Step-by-step explanation:

8 0
4 years ago
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What's the chance of NOT rolling a seven using a pair of dice.
Gemiola [76]

Answer:

5/6

Step-by-step explanation:

total possible = 36

Favorable = 6

1 6

6 1

2 4

4 2

3 4

4 3

Part/whole

6/36

= 1/6

NOT = 5/6

7 0
3 years ago
All 423 Wisconsin public schools were all given a rating by the Wisconsin Department ofPublic Instruction based on several varia
Blizzard [7]

Answer:

z = \frac{\bar X -\mu}{\sigma_{\bar X}}= \frac{70.9-71.5}{0.77}=-0.779

From this result we can conclude that the value of 70.9 is 0.78 deviation below the true mean of 71.5 and that can be considered as unusual. If we conduct a hypothesis test or a confidence interval we will see that we have enough evidence to conclude that the true mean is not significantly different from 71.5.

Step-by-step explanation:

For this case from all the population we know that the population mean and deviation are:

\mu = 71.5,\sigma = 4.87

And we take a random sample of size n =40 and we got a sample mean calculated with the following formula:

\bar X =\frac{\sum_{i=1}^n X_i}{n}= \frac{\sum_{i=1}^{40} X_i}{40}=70.9

And we want to test if this value is unusually low.

Since the sample size is large n>30 we can use the central limit theorem who says that the distribution for the sample mean is given by:

\bar X \sim N (\mu , \frac{\sigma}{\sqrt{n}})

And on this case if we replace the values that we have we got:

\bar X \sim N (\mu_{\bar X}=71.5,\sigma_{\bar X}= \frac{\sigma}{\sqrt{n}}=\frac{4.87}{\sqrt{40}}=0.77)

For this case we can calculate how many deviations above or below is our calculated value from the sample of size 40, using the z score given by:

z = \frac{\bar X -\mu}{\sigma_{\bar X}}= \frac{70.9-71.5}{0.77}=-0.779

From this result we can conclude that the value of 70.9 is 0.78 deviation below the true mean of 71.5 and that can be considered as unusual. If we conduct a hypothesis test or a confidence interval we will see that we have enough evidence to conclude that the true mean is not significantly different from 71.5.

3 0
3 years ago
Tara has a box of 908 beads for an bracelet she wants to put 15 beads on each bracelet what is the greatest number please help m
Cerrena [4.2K]

Answer:

60.53

Step-by-step explanation:

5 0
3 years ago
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