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Likurg_2 [28]
3 years ago
9

Which transformation represents a reflection over the y = x line?

Mathematics
1 answer:
dmitriy555 [2]3 years ago
4 0

Answer:

see explanation

Step-by-step explanation:

Under a reflection in the line y = x

a point (x, y ) → (y, x )

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Solve 2x+2&gt;10<br><br> A. x &lt; 4<br> B. x &gt; 4<br> C. x &gt; 6<br> D. x &lt; 6
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B

Step-by-step explanation:

2x+2>10

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3 years ago
a restroom Holiday Lights blinks once every 3 seconds why is there blue lights blink once every four seconds how many times will
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Answer:

  10 times

Step-by-step explanation:

The lights blink at the same time (if they ever do) every 12 seconds, the least common multiple of the individual times. Then in 120 seconds, they will blink together ...

  120/12 = 10

times.

_____

You could count 11 (simultaneous) blinks, if you count the one at the start of a period of 120 seconds and also the one at the end of that period. If you start marking time between (simultaneous) blinks, you will count only 10.

3 0
3 years ago
The lumen output was determined for each of I = 3 different brands of lightbulbs having the same wattage, with J = 8 bulbs of ea
brilliants [131]

Answer:

Step-by-step explanation:

Hello!

The study variable is

X: Lumen of a bulb of the i brand. i=3

There are 3 populations of bulbs, Brand 1, Brand 2 and brand 3.

The objective is to test if the population means are equal.

The study parameters are:

μ₁: population mean lumen of the population of light bulbs of brand 1.

μ₂: population mean lumen of the population of light bulbs of brand 2.

μ₃: population mean lumen of the population of light bulbs of brand 3.

The hypothesis is:

H₀:μ₁= μ₂= μ₃= μ

H₁: At least one of the population means is different.

To test this hypothesis, considering the given information, I'll use an ANOVA test, then the statistic is defined as:

F= \frac{MSTr}{MSerror}~F_{(I-1)(J-1)}

Rejection region

This region is always one-tailed (right), the statistic is constructed as the mean square of the treatments divided by the mean square of the error, if the number of F is big, this means that the treatments have more effect over the populations. If the value of F is small, this means that there is no difference between the variability caused by the treatments and the one caused by the residues.

Since there is no significance level specified, I'll use α: 0.05

F_{(I-1);(J-1); 1 - \alpha } = F_{2; 7; 0.95} = 19.35

You will reject the null hypothesis when F_{H_0} ≥ 19.35

To calculate the statistic value you need to calculate the Mean Square of Treatments and the Mean Square of errors:

MSTr= SSTr/DfTr = 599.5/2= 299.75

MSerror= SSerror/Dferror= 4776.3/5= 955.26

F_{H_0}= \frac{299.75}{955.26}= 0.31

At this level the decision is to not reject the null hypothesis.

I hope it helps!

4 0
2 years ago
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