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AysviL [449]
3 years ago
7

What is the weight of 2 apples? * .12 .24 16.67 8.33

Mathematics
1 answer:
Crazy boy [7]3 years ago
4 0

Answer:

0.24

Step-by-step explanation:

Have a wonderful day <3

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2 3/10

Step-by-step explanation:


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3 years ago
Read 2 more answers
Answer C,D,E,F<br><br><br>Snsjma
Ulleksa [173]

Answer:

f) 97° = m∠6

e) 83° = m∠5

d) 83° = m∠4

c) 97° = m∠3

b) 97° = m∠2

a) 83° = m∠1

Step-by-step explanation:

  • m∠5 ≅ m∠4; Angle Correspondence Theorem
  • m∠5 ≅ m∠1; Alternate Interior Angles Theorem
  • m∠6 ≅ m∠2; Alternate Exterior Angles Theorem
  • 180° = m∠2 + m∠1; Definition of Linear Pair [Supplementary Angles]
  • 180° = m∠5 + m∠3; Definition of Linear Pair [Supplementary Angles]

I am joyous to assist you anytime.

6 0
3 years ago
Is borrowing money a <br><br> Delegated power <br> Reserved power <br> Concurrent power
grin007 [14]
I believe that it is a concurrent power
8 0
3 years ago
Ten college students were randomly selected. Their grade point averages​ (GPAs) when they entered the program were between 3.5 a
solong [7]

Answer:

The 95% confidence interval for the true slope is (0.03985, 0.14206).

Step-by-step explanation:

For the regression equation:

\hat y=\alpha +\hat \beta x

The (1 - <em>α</em>)% confidence interval for the regression coefficient or slope (\hat \beta ) is:

Ci=\hat \beta \pm t_{\alpha/2, (n-2)}\times SE(\hat \beta )

The regression equation for current GPA (Y) of students based on their GPA's when entering the program (X) is:

\hat Y=3.584756+0.090953 X

The summary of the regression analysis is:

Predictor          Coefficient             SE             t-stat            p-value

Constant             3.584756          0.078183       45.85075      5.66 x 10⁻¹¹

Entering GPA   0.090953          0.022162        4.103932       0.003419

The regression coefficient and standard error are:

\hat \beta = 0.090953\\SE (\hat \beta)=0.022162

The critical value of <em>t</em>  for 95% confidence level and 8 degrees of freedom is:

t_{\alpha/2, n-2}=t_{0.05/2, 10-2}=t_{0.025, 8}=2.306

Compute the 95% confidence interval for (\hat \beta ) as follows:

CI=\hat \beta \pm t_{\alpha/2, (n-2)}\times SE(\hat \beta )\\=0.090953\pm 2.306\times 0.022162\\=0.090953\pm 0.051105572\\=(0.039847428, 0.142058572)\\\approx (0.03985, 0.14206)

Thus, the 95% confidence interval for the true slope is (0.03985, 0.14206).

6 0
3 years ago
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anygoal [31]

the answer should be the third option


6 0
3 years ago
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