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slava [35]
3 years ago
5

Simplify the expression: 15−3[2+6(−3)]

Mathematics
2 answers:
Sedaia [141]3 years ago
6 0
The correct answer is 63 i hope this helps out, have a nice day!!!
SpyIntel [72]3 years ago
4 0
63 is the answer
<span>Unary minus: -3Multiple: 6 * (-3) = -18Add: 2 + (-18) = -16Multiple: 3 * (-16) = -48<span>Subtract: 15 - (-48) = 63
hope it helps :)
im only a 6th grader so sorry if its wrong</span></span>
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Which value of the vanable is a solution of the inequality? t&lt;-6<br> 7<br> 6<br> -6<br> -7
oksian1 [2.3K]

Answer:

-7

Step-by-step explanation:

-7 is a solution of the inequality t<-6

By the way, for the number -6, you can think about a temperature below zero. When it is freezing 6 degrees below zero (-6) it is pretty cold.

The question is which number(s) can you substitute for t so that the formula (the inequality) is True.

So let's try for each given value and substitute it for t in t<-6

if you substitute 7 for t you get this:

Is 7 smaller then -6 ?

No that is not true because 7 is bigger then -6.

if you substitute 7 for t you get this:

Is 7 smaller then -6 ?

No that is not true because 7 is much bigger then -6.

if you substitute 6 for t you get this:

Is 6 smaller then -6 ?

No that is not true because 6 is much bigger then -6.

if you substitute -6 for t you get this:

Is -6 smaller then -6 ?

No, that is NOT true because -6 is exactly the same as -6 but NOT smaller then -6...

if you substitute-7 for t you get this:

Please think about temperatures below zero again.

Is -7 colder the -6 ? If so, then the statement is true...

Is -7 smaller then -6 ?

Yes that is true!

So -7 is a solution of the inequality t<-6

6 0
3 years ago
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Fantom [35]

Answer:

It should be C

Step-by-step explanation:

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Answer:

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Step-by-step explanation:

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Which characteristic of a data set makes a linear regression model unreasonable?
LiRa [457]

Which characteristic of a data set makes a linear regression model unreasonable?

Answer: A correlation coefficient close to zero makes a linear regression model unreasonable.

If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important check is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.

Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.

6 0
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Write an equation to describe the proportional relationship in this table. Explain your thinking and how you got your answer.
creativ13 [48]

Focus on the values in red outside the table (on the left and right sides). As the output increases by 4, the input increases by 1. This leads to the slope being rise/run = 4/1 = 4. The slope is the number just to the left of the x variable. So that's how they ended up with the equation y = 4x.

You can think of it as y = 4x+0, and note how it's in the form y = mx+b

m = 4 = slope

b = 0 = y intercept

The y intercept is the value of y when x = 0.

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Now because x = 0 and y = 0 pair up together, we can find the slope a different way: Pick any row other than the first row. Divide the y value over its paired x value. So let's say we pick on row two and we'd get a slope of y/x = 4/1 = 4.

Or we could pick on row three and get y/x = 8/2 = 4.

Picking on the fourth row gets us the slope to be y/x = 12/3 = 4. We end up with the same slope value each time. Again, this trick only works if (x,y) = (0,0) is on the line. Otherwise, you'll need to use the first method or use the slope formula.

For equations like this, we consider them a direct proportion. As x increases, so does y. As x increases by 1, y increases by 4. This is the same throughout the table.

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A real world example of this could be that x represents the number of sodas you buy, and if each soda is $4, then y = 4x represents the total cost of buying x number of sodas.

For instance, if you bought x = 10 sodas, then y = 4*x = 4*10 = 40 dollars is what you spend overall.

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