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horsena [70]
3 years ago
9

What is 9 to the first power times (-2)3? (A) -27 (B) 36 (C) -72 (D) 27

Mathematics
2 answers:
Greeley [361]3 years ago
8 0

Answer:

-72

Step-by-step explanation:

9*(-2)³ = 9*(-8) = -72

Goshia [24]3 years ago
8 0

Answer:

(C) -72

Step-by-step explanation:

9^1*(-2)^3

Any number to the exponent of 1 is equal to themselves

= 9*(-2)^3

Solve the exponent and multiply

= 9*(-8)\\=-72

I hope this helps!

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An interior automotive supplier places several electrical wires in a harness.Apull test measures the force required to pull spli
oksano4ka [1.4K]

Answer:

a) For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assumin Normal distribution

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical dsitribution

The result is on the figure attached.

b) For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.

Step-by-step explanation:

For this case we have the following data:

28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4

The quantile-quantile or q-q plot is a graphical procedure in order to check the validity of a distributional assumption for a data set. We just need to calculate "the theoretically expected value for each data point based on the distribution in question".

If the values are asusted to the assumed distribution, we will see that "the points on the q-q plot will fall approximately on a straight line"

For this case our distribution assumed is normal.

Part a

For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assuming Normal distribution (0,1)

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical distribution

The result is on the figure attached.

Part b

For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.

4 0
3 years ago
Help me please (I need the answer asap...)
Roman55 [17]
Answer: x = 6
x+x=19-7
2x=12
Hence the answer is x=6
5 0
3 years ago
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(2ax)^3 I NEED THE ANSWER ASAP
weeeeeb [17]

Answer:

Then answer will still be the same, unless you have a number for a and x to multiply it

Step-by-step explanation:

4 0
3 years ago
PLEASE HELP!! brainliest if correct!!
Sonja [21]
Graph #1: No
Graph #2: Yes
Graph #3: No
Graph #4: No
Graph #5: No
Graph #6: Yes

Reasoning:

The vertical line test is a test that determines wether a graph is a function or a relation. The vertical line test shows that if you construct a vertical line through any point on the graph, then the vertical line should only intercept the graph once for it to be a function.
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If y = -4 when x = 10, find y when x = 5
vesna_86 [32]
To find Y you must divide two by each side, making y=-2
- I hope this helps :)
3 0
3 years ago
Read 2 more answers
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