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olasank [31]
3 years ago
11

A line segment is sometimes/never/always similar to another line segment, because we can sometimes/never/always map one onto the

other using only dilations and rigid transformations.
Mathematics
2 answers:
iVinArrow [24]3 years ago
7 0

Answer: sometimes for both

Step-by-step explanation:

svetlana [45]3 years ago
6 0

Answer: "always" for both

A line segment is <u>always</u> similar to another line segment, because we can <u>always</u> map one onto the other using only dilations and rigid transformations.

==================================

Explanation:

A dilation is where we grow or shrink an object. In this case, it would be lengthening or shortening a line. We can dilate any line to get it to any desired length we want. Then to make sure it matches up perfectly with the other line, we can perform translations (aka shifting) and rotations.

In other words, if we have four points A,B,C,D then it is possible to use dilations and rigid transformations to map points A,B to points C,D. The first segment AB would map to segment CD.

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the dimensions of the oven tray is 600mm by 500mm. Each cake tin is 25cm in diameter. How many cake tins can be fit on the oven
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Which number sentence correctly solves this problem? There were 52,165 people at the soccer game on Friday. There were 49,872 pe
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8 0
3 years ago
. (0.5 point) We simulate the operations of a call center that opens from 8am to 6pm for 20 days. The daily average call waiting
SashulF [63]

Answer:

The 95% t-confidence interval for the difference in mean is approximately (-2.61, 1.16), therefore, there is not enough statistical evidence to show that there is a change in waiting time, therefore;

The change in the call waiting time is not statistically significant

Step-by-step explanation:

The given call waiting times are;

24.16, 20.17, 14.60, 19.79, 20.02, 14.60, 21.84, 21.45, 16.23, 19.60, 17.64, 16.53, 17.93, 22.81, 18.05, 16.36, 15.16, 19.24, 18.84, 20.77

19.81, 18.39, 24.34, 22.63, 20.20, 23.35, 16.21, 21.73, 17.18, 18.98, 19.35, 18.41, 20.57, 13.00, 17.25, 21.32, 23.29, 22.09, 12.88, 19.27

From the data we have;

The mean waiting time before the downsize, \overline x_1 = 18.7895

The mean waiting time before the downsize, s₁ = 2.705152

The sample size for the before the downsize, n₁ = 20

The mean waiting time after the downsize, \overline x_2 = 19.5125

The mean waiting time after the downsize, s₂ = 3.155945

The sample size for the after the downsize, n₂ = 20

The degrees of freedom, df = n₁ + n₂ - 2 = 20 + 20  - 2 = 38

df = 38

At 95% significance level, using a graphing calculator, we have; t_{\alpha /2} = ±2.026192

The t-confidence interval is given as follows;

\left (\bar{x}_{1}- \bar{x}_{2}  \right )\pm t_{\alpha /2}\sqrt{\dfrac{s_{1}^{2}}{n_{1}}+\dfrac{s_{2}^{2}}{n_{2}}}

Therefore;

\left (18.7895- 19.5152 \right )\pm 2.026192 \times \sqrt{\dfrac{2.705152^{2}}{20}+\dfrac{3.155945^2}{20}}

(18.7895 - 19.5125) - 2.026192*(2.705152²/20 + 3.155945²/20)^(0.5)

The 95% CI = -2.6063 < μ₂ - μ₁ < 1.16025996668

By approximation, we have;

The 95% CI = -2.61 < μ₂ - μ₁ < 1.16

Given that the 95% confidence interval ranges from a positive to a negative value, we are 95% sure that the confidence interval includes '0', therefore, there is sufficient evidence that there is no difference between the two means, and the change in call waiting time is not statistically significant.

6 0
2 years ago
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