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MariettaO [177]
2 years ago
5

What must be true if

{y}" align="absmiddle" class="latex-formula"> / \frac{3a}{b} =\frac{3a}{b}? Assume a\neq0, b\neq0, and y\neq0.

Mathematics
1 answer:
Nesterboy [21]2 years ago
6 0

Answer:

4th option is correct

Step-by-step explanation:

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Heyyy.... can someone help plz thx
blagie [28]

Answer:

When a point gets reflected across the x-axis, the sign of its y-coordinate changes so the coordinates of Q' are (3, 4).

4 0
3 years ago
Read 2 more answers
Help! <br><br>3x10=(2x10)+(1x_)
motikmotik
3*10=(2*10)+(1*x) \\  \\ 30=20+x \\  \\ 10=x
8 0
2 years ago
Help please (will chose brainliest).
lara [203]
Answers with Explanation.


i. If we raise a number to an exponent of 1, we get the same number.

{10}^{1}  = 10

ii. If we raise 10 to an exponent of 2, it means we multiply 10 by itself two times.

{10}^{2}  = 10 \times 10 = 100

iii. If we raise 10 to an exponent of 3, it means we multiply 10 by itself three times.



{10}^{3}  = 10 \times  {10}^{2}  = 10 \times 100 = 1000

iv. If we raise 10 to an exponent of 4, it means we multiply 10 by itself four times.


{10}^{4}  =  10 \times {10}^{3} = 10 \times 1000 =  10000

v. If we raise 10 to an exponent of 5, it means we multiply 10 by itself five times.



{10}^{5}  = 10 \times  {10}^{4}  = 10 \times 10000 = 100000

{10}^{5}  = 100000

vi. Recall that,

{a}^{ - m}  =  \frac{1}{ {a}^{m} }
We apply this law of exponents to obtain,

{10}^{ - 2}  =  \frac{1}{{10}^{2} }  =  \frac{1}{100}

vii. We apply
{a}^{ - m}  =  \frac{1}{ {a}^{m} }
again to obtain,


{10}^{ - 3}  =  \frac{1}{ {10}^{3} }  =  \frac{1}{1000}





5 0
3 years ago
.For small training sets variance may contribute more to the overall error than bias. Sometimes this is handled by reducing the
Ymorist [56]

Answer:

Bias is the difference between the average prediction of our model and the correct value which we are trying to predict and variance is the variability of model prediction for a given data p[oint or a value which tells us the spread of our data the variance perform very well on training data but has high error rates on test data on the other hand if our model has small training sets then it's going to have smaller variance & & high bias and its contribute more to the overall error than bias. If our model is too simple and has very few parameters then it may have high bias and low variable. As the model go this is conceptually trivial and is much simpler than what people commonly envision when they think of modelling but it helps us to clearly illustrate the difference bewteen bias & variance.

3 0
2 years ago
Two gears in a machine are aligned by a mark drawn from the center of one gear to the center of the other. If the first gear has
scoray [572]

Answer:

The firstgear needs to make five revolutions in order for the marks to line up again.

Step-by-step explanation:

4 0
3 years ago
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