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4vir4ik [10]
3 years ago
15

How does knowing the double 6+6=12 help you solve the near double 6+7=13

Mathematics
1 answer:
forsale [732]3 years ago
8 0

Answer:

6 + 7 = 13

Step-by-step explanation:

We are given the following information in the question:

We know that

6 + 6 = 12

We need this information to evaluate

6+7

The evaluation can be done with the help of using associative property and distributive property.

Associative property: (a + b) + c = a + (b + c)

The evaluation can be shown as:

6 + 7\\= 6 + 6 + 1\\=(6 + 6) + 1\\= 12 + 1\\=13

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inysia [295]

Answer:

The coupon was for 25% off

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3 years ago
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Given the equation:
Alisiya [41]

Answer:

x = 1 and x = \frac{-4}{5}

Step-by-step explanation:

In this equation, a=5, b=-1, c=-4.

Plug these into the quadratic formula:

x = \frac{1+\sqrt{-1^{2}-(-4)(5)(-4) } }{2(5)}   and x = \frac{1-\sqrt{-1^{2}-(-4)(5)(-4) } }{2(5)}

Now, simplify the equations:

x = \frac{1+\sqrt{81} }{10} = \frac{1+9}{10} = \frac{10}{10} = 1

and

x = \frac{1-\sqrt{81} }{10} = \frac{1-9}{10} = \frac{-8}{10} = \frac{-4}{5}

5 0
4 years ago
A large manufacturer that sells consumer products on-line wishes to publicize its customer satisfaction in an advertisement. Spe
sergejj [24]

Answer:

z=\frac{0.93 -0.9}{\sqrt{\frac{0.9(1-0.9)}{400}}}=2  

p_v =P(z>2)=0.0228  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people who say yes is significantly higher than 0.9 or 90%.

Step-by-step explanation:

Data given and notation

n=400 represent the random sample taken

X=372 represent the number of people who say yes

\hat p=\frac{372}{400}=0.93 estimated proportion of people who say yes

p_o=0.9 is the value that we want to test

\alpha represent the significance level

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that that more than 90% of its costumers would tell their friend to buy a product from the manufacturer.:  

Null hypothesis:p\leq 0.9  

Alternative hypothesis:p > 0.9  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

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

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.93 -0.9}{\sqrt{\frac{0.9(1-0.9)}{400}}}=2  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level assumed for this case is \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a right tailed test the p value would be:  

p_v =P(z>2)=0.0228  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people who say yes is significantly higher than 0.9 or 90%.

8 0
3 years ago
What is the probability of flipping both heads with two different coin
GuDViN [60]
25% chance.
There is a 50% chance to land a head for one coin. Divide that by 2 to get 25%
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The kiwi are 50 cents each. Therefore, Lisa can buy ten kiwi. What did you mean by the examples?
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