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bezimeni [28]
1 year ago
9

Anyone think they can help me??

Mathematics
1 answer:
dem82 [27]1 year ago
6 0

The kind of transformation that is illustrated based on the information given is reflection.

<h3>What is transformation?</h3>

It should be noted that transformation simply means the change in the position of an object while maintaining the length and other properties.

In this case, the kind of transformation that is illustrated based on the information given is reflection.

This is the flipping of the pre image and then producing the mirror image.

Here, there'll be no change in the shape of the size. This depicts congruency.

Learn more about transformation on:

brainly.com/question/4289712

#SPJ1

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A bag contains 100 ounces of birdseed.
Valentin [98]

Answer:

H

Step-by-step explanation:

5 0
3 years ago
Solve 4 sec sqrd x = 8
Aneli [31]

                                                <u>4 sec²(x)  =  8</u>

Divide each side by  4:                   sec²(x) = 2

Take the square root of each side:    sec(x) = + or - √2

We know that sec(x) = 1/cos(x)

So the equation becomes                1/cos(x) = + or - √2

Divide '1' by each side:                    cos(x)  =  + or -  (1/2) √2

       x =  <em>45°,  135°,  225°,  315°


</em>
8 0
4 years ago
You are collecting a sample of 60 data points from a population that you know to follow an exponential distribution. It is not a
11111nata11111 [884]

Answer:

For the exponential distribution:

\mu = \frac{1}{\lambda}

\sigma^2 = \frac{1}{\lambda^2}

We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.

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

\mu_{\bar X} = \bar X

\sigma_{\bar X}= \frac{\sigma}{\sqrt{n}}

Step-by-step explanation:

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

For this case we have a large sample size n =60 >30

The exponential distribution is the probability distribution that describes the time between events in a Poisson process.

For the exponential distribution:

\mu = \frac{1}{\lambda}

\sigma^2 = \frac{1}{\lambda^2}

We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.

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

\mu_{\bar X} = \bar X

\sigma_{\bar X}= \frac{\sigma}{\sqrt{n}}

5 0
4 years ago
Simplify the above question​
ankoles [38]

Answer:

0.75417552

reduced equals 0.75

Step-by-step explanation:

log(55/2)

log(81)

Decimal Form: 0.7541755

this answer is the anser if you are dividing log 10 and 27 1/3 by log 10 81

6 0
3 years ago
Which expression is equivalent to StartFraction RootIndex 4 StartRoot 6 EndRoot Over RootIndex 3 StartRoot 2 EndRoot?
Vika [28.1K]
4 start root hope it helps
3 0
3 years ago
Read 2 more answers
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