pasha is thinking of a number such that when twice the number is added to three times one more than the number she gets the same
2 answers:
Answer:
The number is -7.
Step-by-step explanation:
Let the number be = x
when twice the number is added to three times one more than the number. Mathematically, we can denote this as:
She gets the same result as when she multiplies four times one less than the number.
Now, both the results are same, so we will equate them same.
=>
=>
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This gives x = -7
So, the number Pasha was thinking was -7.
We can check this:
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=> (checked)
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Answer:
Step-by-step explanation:
We can solve this multiplication of polynomials by understanding how to multiply these large terms.
To multiply two polynomials together, we must multiply each term by each term in the other polynomial. Each term should be multiplied by another one until it's multiplied by all of the terms in the other expression.
- <em>We can do this by focusing on one term in the first polynomial and multiplying it by </em><em>all the terms</em><em> in the second polynomial. We'd then repeat this for the remaining terms in the second polynomial.</em>
Let's first start by multiplying the first term of the first polynomial, , by all of the terms in the second polynomial. (
)
Now, we can add up all these expressions to get the first part of our polynomial. Ordering by exponent, our expression is now
Now let's do the same with the second term () and the third term (
).
- Adding on to our original expression:
- Adding on to our original expression:
Phew, that's one big polynomial! We can simplify it by combining like terms. We can combine terms that share the same exponent and combine them via their coefficients.
This simplifies our expression down to .
Hope this helped!
The best answer from the options that proves that the residual plot shows that the line of best fit is appropriate for the data is: ( Statement 1 ) Yes, because the points have no clear pattern
X Given Predicted Residual value
1 3.5 4.06 -0.56
2 2.3 2.09 0.21
3 1.1 0.12 0.98
4 2.2 -1.85 4.05
5 -4.1 -3.82 -0.28
The residual value is calculated as follows using this formula: ( Given - predicted )
1) ( 3.5 - 4.06 ) = -0.56
2) ( 2.3 - 2.09 ) = 0.21
3) ( 1.1 - 0.12 ) = 0.98
4) (2.2 - (-1.85) = 4.05
5) ( -4.1 - (-3.82) = -0.28
Residual values are the difference between the given values and the predicted values in a given data set and the residual plot is used to represent these values .
attached below is the residual plot of the data set
hence we can conclude from the residual plot attached below that the line of best fit is appropriate for the data because the points have no clear pattern ( i.e. scattered )
learn more about residual plots : brainly.com/question/16821224
