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bogdanovich [222]
4 years ago
8

Multiply. −2x(6 x 4 −7 x 2 +x−5) explain plzz

Mathematics
1 answer:
Korolek [52]4 years ago
3 0
The way u wrote it doesn't make sense 
but u should combine like terms. then multiply regularly. hope this helps

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A line of best fit predicts that when x equals 30, y will equal 34.215, but y actually equals 32. What is the residual in this c
Katarina [22]

Answer: A. - 2.215

Step-by-step explanation:

• A residual is the difference between the actual value and the predicted value in a regression model. It represents the vertical distance from the actual point to the point on the regression line.

\text{Residual=Actual value of y -predicted value of y}\\\\\Rightarrow\text{Residual}=32-34.215\\\\\Rightarrow\text{Residual}=-2.215

Hence, the residual in this case = -2.215

4 0
3 years ago
Write a polynomial function with zeros -3,5,8​
klemol [59]

Answer:

x^3-10x^2+x+120

Step-by-step explanation:

Assuming you mean roots -3, 5, 8

These happen when we have (x+3)(x-5)(x-8)=0

Expand this

(x^2-2x-15)(x-8)=0

=x^3-2x^2-15x-8x^2+16x+120

=x^3-10x^2+x+120

3 0
3 years ago
Which of the following is not a method used to prove triangles congruent
RSB [31]
Your answer is D. SSA Postulate because it doesn't exist!
3 0
4 years ago
Could someone help me please ? :)
Degger [83]

ANSWER = 17.5% of 360 = 63

EXPLANATION:

Find 10% of 360 = 36

Then 5% of 360 = 18

Then 2.5% of 360 = 9

Add them together

so 17.5% of 360 = 63

8 0
3 years ago
Construct a 90% confidence interval for μ1-μ2 with the sample statistics for mean calorie content of two​ bakeries' specialty pi
DIA [1.3K]

Answer:

The 90% confidence interval for the difference in mean (μ₁ - μ₂) for the two bakeries is; (<u>49</u>) < μ₁ - μ₂ < (<u>289)</u>

Step-by-step explanation:

The given data are;

Bakery A

\overline x_1<em> </em>= 1,880 cal

s₁ = 148 cal

n₁ = 10

Bakery B

\overline x_2<em> </em>= 1,711 cal

s₂ = 192 cal

n₂ = 10

\left (\bar{x}_1-\bar{x}_{2}  \right ) - t_{c}\cdot \hat \sigma \sqrt{\dfrac{1}{n_{1}}+\dfrac{1}{n_{2}}}< \mu _{1}-\mu _{2}< \left (\bar{x}_1-\bar{x}_{2}  \right ) + t_{c}\cdot \hat \sigma \sqrt{\dfrac{1}{n_{1}}+\dfrac{1}{n_{2}}}

df = n₁ + n₂ - 2

∴ df = 10 + 18 - 2 = 26

From the t-table, we have, for two tails, t_c = 1.706

\hat{\sigma} =\sqrt{\dfrac{\left ( n_{1}-1 \right )\cdot s_{1}^{2} +\left ( n_{2}-1 \right )\cdot s_{2}^{2}}{n_{1}+n_{2}-2}}

\hat{\sigma} =\sqrt{\dfrac{\left ( 10-1 \right )\cdot 148^{2} +\left ( 18-1 \right )\cdot 192^{2}}{10+18-2}}= 178.004321469

\hat \sigma ≈ 178

Therefore, we get;

\left (1,880-1,711  \right ) - 1.706\times178 \sqrt{\dfrac{1}{10}+\dfrac{1}{18}}< \mu _{1}-\mu _{2}< \left (1,880-1,711  \right ) + 1.706\times178 \sqrt{\dfrac{1}{10}+\dfrac{1}{18}}

Which gives;

169 - \dfrac{75917\cdot \sqrt{35} }{3,750} < \mu _{1}-\mu _{2}< 169 + \dfrac{75917\cdot \sqrt{35} }{3,750}

Therefore, by rounding to the nearest integer, we have;

The 90% C.I. ≈ 49 < μ₁ - μ₂ < 289

4 0
3 years ago
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