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Anvisha [2.4K]
4 years ago
7

Figure that represents 150%

Mathematics
1 answer:
diamong [38]4 years ago
5 0
Suppose a square is 100%, 50%: the square is divided into two equal parts, and one of them is shaded, therefore it is 50%. 25%: the square is divided into 4 equal parts, and one of them is shaded, therefore it is 25%. 150%: there are two squares, each divided into 2 equal parts, and 3 of them is shadowed, therefore it is 150%

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Which rational number is NOT greater than point A?
kramer

Step-by-step explanation:

) Every positive rational number is greater than 0. 

(ii) Every negative rational number is less than 0.

(iii) Every positive rational number is greater than every negative rational number. 

(iv) Every rational number represented by a point on the number line is greater than every rational number represented by points on its left. 

(v) Every rational number represented by a point on the number line is less than every rational number represented by paints on its right

b

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4 years ago
Yoooooooooooooooooooooooooo can you please help me!?
klemol [59]
She has totally 10+5+3=18 marbles, so the probability is 10/18=5/9. The complement is (9-5)/9=4/9.

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4 0
3 years ago
Please help asap…………
finlep [7]

Step-by-step explanation:

the most common form of line equation is

y = ax + b

a is the slope of the line. it is expressed as the ratio

y coordinate change / x coordinate change

when going from one point to the other.

b is the y-intercept (the y value when x = 0).

so, in our case, the slope is 2, the y-intercept is -3.

the y-intercept gives you the first point : (0, -3)

using the slope of 2 we know that for every unit x increases, y increases by 2.

so, you can pick a next point e.g. x = 2, which makes y = -3 + 2×2 = -3 + 4 = 1

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4 0
2 years ago
Insect flies 20ft in 1sec. What is that in miles per hour?
vladimir2022 [97]
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6 0
3 years ago
The following table summarises the data from a survey on the ownership of iPods among families with different levels of income.
AURORKA [14]

The two nominal variables are related.

The following table summarises the data from a survey on the ownership of iPods among families with different levels of income.  

Ownership           C1                  C2                  C3

No                         40                 32                   48

Yes                        30                 48                   52

The first thing to do in order to determine if they are related or not is to state our null and alternative hypothesis

Null hypothesis

\mathbf{H_o: Two \nomial  \ variables  \ are \  related}

Alternative hypothesis

\mathbf{H_a: Two \nomial  \ variables  \ are \  not \  related}

Using the Chi-square test statistics which can be expressed by using the formula  

X ^2 = \sum \dfrac{(O-E)^2}{E}

Ownership           C1                  C2                  C3                  Total

No                         40                 32                   48                 120

Yes                        30                 48                   52                 130

Total                      70                 80                   100                250

The expected values are calculated as:

\mathsf{E_{a,b} = \dfrac{(row \ total \times column \ total )}{grand \ total }}

\mathsf{E_{1,1} = \dfrac{(70 \times120 )}{250 }}

\mathsf{E_{1,1} = 33.6}

\mathsf{E_{1,2} = \dfrac{(70 \times130 )}{250 }}

\mathsf{E_{1,2} = 36.4}

\mathsf{E_{2,1} = \dfrac{(80 \times120 )}{250 }}

\mathsf{E_{2,1} = 38.4}

\mathsf{E_{2,2} = \dfrac{(80 \times 130 )}{250 }}

\mathsf{E_{2,2} = 41.6}

\mathsf{E_{3,1} = \dfrac{(100 \times120 )}{250 }}

\mathsf{E_{3,1} = 48}

\mathsf{E_{3,2} = \dfrac{(70 \times130 )}{250 }}

\mathsf{E_{3,2} = 52}

∴ Using the Chi-square test statistics, we have:

X ^2 = \sum \dfrac{(O-E)^2}{E}

X ^2 = \Bigg(  \dfrac{(40-33.6)^2}{33.6}+   \dfrac{(30-36.4)^2}{36.4}+   \dfrac{(32-38.4)^2}{38.4}+  \dfrac{(48-41.6)^2}{41.6} +   \dfrac{(48-48)^2}{48}+   \dfrac{(52-52)^2}{52} \Bigg)

X ^2 = \Bigg(  \dfrac{40.96}{33.6}+   \dfrac{40.96}{36.4}+   \dfrac{40.96}{38.4}+  \dfrac{40.96}{41.6} +   \dfrac{0}{48}+   \dfrac{0}{52} \Bigg)

X ^2 = \Bigg(  1.2190+   1.1253+  1.0667+ 0.9846+0+ 0 \Bigg)

\mathbf{X ^2 =4.3956}

The degree of freedom df = ((r - 1) × (c - 1))

= (3 - 1) (2 -1 )

= 2 × 1

= 2

∴

Assuming the level of significance = 5%

The p-value of the Chi-square test statistics at df of 2 is:

= \mathbf{P(X^2 > 4.3956) \implies 0.111}

Therefore, we can conclude that since the p-value (0.111) is greater than the level of significance (0.05), we fail to reject the null hypothesis.

Hence, the two nominal variables are related.

Learn more about Chi-square test statistics here:

brainly.com/question/2365682?referrer=searchResults

7 0
3 years ago
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