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kozerog [31]
3 years ago
10

Solve each proportion. show your work. 2x/7 = 12/14

Mathematics
1 answer:
dybincka [34]3 years ago
8 0
2x/7 = 12/14
Multiply both sides of the equation by 7:
2x = 84/14
Simplify:
2x = 6
Divide both sides by 2 and your answer is....
x = 3
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Find the common difference for the infinite arithmetic sequence shown.
mihalych1998 [28]

The common difference is 12

Further explanation:

It is given that the infinite sequence is an arithmetic sequence

The common difference is the difference between consecutive terms of an arithmetic sequence.

Here,

a_1 = 211\\a_2 = 223\\a_3 = 235\\a_4 = 247........

The common difference is denoted by d.

Here,

d = a_2-a_1 = 223-211 = 12\\a_3-a_2 = 235-223 = 12

The common difference is same for all proceeding terms.

So,

d = 12

Keywords: Infinite arithmetic sequence, Common difference

Learn more about arithmetic sequence at:

  • brainly.com/question/12613605
  • brainly.com/question/1284310

#LearnwithBrainly

4 0
3 years ago
If someone can help pls need soon
Annette [7]

Answer:

Step-by-step explanation:

7 0
2 years ago
One leg of a right triangle is 4 cm the hypotenuse is 10 cm how long it the other leg
ASHA 777 [7]
I hope this will work.
3 0
3 years ago
Read 2 more answers
Solve the equation for all real solutions.<br> 8w2 + 2w + 2 = 3
fredd [130]

Answer:

Step-by-step explanation:

w=  1 /4   or w=  −1/ 2

3 0
3 years ago
A random sample of 25 ACME employees showed the average number of vacation days taken during the year is 18.3 days with a standa
Norma-Jean [14]

Answer:

a) Null hypothesis:\mu \leq 15  

Alternative hypothesis:\mu > 15  

b) df=n-1=25-1=24  

For this case the p value is given p_v = 0.0392

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 15 at 5% of signficance.  

c) Type I error, also known as a “false positive” is the error of rejecting a null  hypothesis when it is actually true. Can be interpreted as the error of no reject an  alternative hypothesis when the results can be  attributed not to the reality.

So for this case a type I of error would be reject the hypothesis that the true mean is less or equal than 15 and is actually true.

Step-by-step explanation:

Data given and notation  

\bar X=18.3 represent the sample mean

s=3.72 represent the sample standard deviation

n=25 sample size  

\mu_o =15 represent the value that we want to test

\alpha=0.05 represent the significance level for the hypothesis test.  

t would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

Part a: State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the true mean for vacation days is higher than 15, the system of hypothesis would be:  

Null hypothesis:\mu \leq 15  

Alternative hypothesis:\mu > 15  

If we analyze the size for the sample is < 30 and we don't know the population deviation so is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:  

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}  (1)  

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Part b: P-value  and conclusion

The first step is calculate the degrees of freedom, on this case:  

df=n-1=25-1=24  

For this case the p value is given p_v = 0.0392

Conclusion  

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is higher than 15 at 5% of signficance.  

Part c

Type I error, also known as a “false positive” is the error of rejecting a null  hypothesis when it is actually true. Can be interpreted as the error of no reject an  alternative hypothesis when the results can be  attributed not to the reality.

So for this case a type I of error would be reject the hypothesis that the true mean is less or equal than 15 and is actually true.

3 0
3 years ago
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