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Trava [24]
3 years ago
9

What are two ratios that are equivalent to 9/12

Mathematics
2 answers:
Gnom [1K]3 years ago
6 0
Find the greatest common factor (GCF) of 9 and 12 using factor trees. The GCF is 3

Divide each term (9 and 12) over 3
9/3 = 3
12/3 = 4

So 9/12 reduces to 3/4

In other words, 9/12 = 3/4

--------------------------------------

Now focusing on 3/4, we can multiply top and bottom by the same value. Let's say we multiply top and bottom by 5

3*5 = 15
4*5 = 20

So 3/4 = 15/20

--------------------------------------

So two ratios equivalent to 9/12 are 3/4 and 15/20. There are infinitely other ratios that are equivalent. 

In short, the answers are 3/4 and 15/20.
Mrac [35]3 years ago
4 0
18/24 and 3/4 are ratios that are equivalent
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3 years ago
A random sample of 144 recent donations at a certain blood bank reveals that 81 were type A blood. Does this suggest that the ac
Reptile [31]

Answer:

Null hypothesis:p=0.4  

Alternative hypothesis:p \neq 0.4

z=\frac{0.5625 -0.4}{\sqrt{\frac{0.4(1-0.4)}{144}}}=3.98  

p_v =2*P(z>3.98)=0.0000689  

Since the p value is very low compared to the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true percent of people with type A of blood is significantly different from 0.4 or 40%

Step-by-step explanation:

Information given

n=144 represent the random sample taken

X=81 represent the number of people with type A blood

\hat p=\frac{81}{144}=0.5625 estimated proportion of  people with type A blood

p_o=0.4 is the value that we want to verify

\alpha=0.01 represent the significance level

z would represent the statistic

p_v{/tex} represent the p value Hypothesis to testWe want to test if the percentage of the population having type A blood is different from 40%.:  Null hypothesis:[tex]p=0.4  

Alternative hypothesis:p \neq 0.4  

the statistic is given by:

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

Replacing the info given we got:

z=\frac{0.5625 -0.4}{\sqrt{\frac{0.4(1-0.4)}{144}}}=3.98  

Now we can calculate the p value with this probability taking in count the alternative hypothesis:

p_v =2*P(z>3.98)=0.0000689  

Since the p value is very low compared to the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true percent of people with type A of blood is significantly different from 0.4 or 40%

3 0
3 years ago
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