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iris [78.8K]
3 years ago
15

Simplify. 2(3v+1) – 5

Mathematics
2 answers:
fomenos3 years ago
6 0
I it helps you get it right

Degger [83]3 years ago
4 0

Answer:

1/2

Step-by-step explanation:

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11.1/0.01= what is the answer
andrew-mc [135]
Answer: 1,110
11.1/.01=1,110
5 0
3 years ago
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For questions 1 and 2, multiple answers may be selected
d1i1m1o1n [39]

The discrete data is (b) while the continuous data are (a) and (d)

<h3>What are discrete data?</h3>

These are data that can be represented using positive whole numbers.

Using the above definition as a guide, the discrete data is (b) The number of books in your apartment

<h3>What are continuous data?</h3>

These are data that can be represented using decimal numbers.

Using the above definition as a guide, the continuous data are (a) The weight of cows  and (d) The ounces of water that you drink each day

Read more about discrete data at:

brainly.com/question/4811422

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6 0
2 years ago
3f+2g=30 and f+2g=26
tatuchka [14]
3f + 2g = 30 . . .(1)
f + 2g = 26 . . . .(2)

(1) - (2) => 2f = 4 => f = 4/2 = 2

From (2), 2 + 2g = 26 => 2g = 26 - 2 = 24 => g = 24/2 = 12

Therefore, f = 2 and g = 12
7 0
3 years ago
Round 29.383 to the nearest whole number
lisov135 [29]

Answer:

29

Step-by-step explanation:

It doesnt round up because its under 29.5

therefore it goes down to 29

7 0
3 years ago
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A sample of 1200 computer chips revealed that 45% of the chips fail in the first 1000 hours of their use. The company's promotio
yaroslaw [1]

Answer:

z=\frac{0.45 -0.48}{\sqrt{\frac{0.48(1-0.48)}{1200}}}=-2.08

p_v = P(Z

So the p value obtained was a low value and using 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, and we can said that at 5% of significance the proportion of chips that fail in the first 1000 hours of their use is not significantly less than 0.48.   

Step-by-step explanation:

Data given and notation

n=1200 represent the random sample taken

\hat p=0.45 estimated proportion of chips that fail in the first 1000 hours of their use

\mu_0 =0.48 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

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 the true proportion si less then 0.48:  

Null hypothesis:p\geq 0.48  

Alternative hypothesis:p < 0.48  

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  is significantly different from a hypothesized value .

Calculate the statistic  

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

z=\frac{0.45 -0.48}{\sqrt{\frac{0.48(1-0.48)}{1200}}}=-2.08

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 provided \alpha=0.05. The next step would be calculate the p value for this test.  

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

p_v = P(Z

So the p value obtained was a low value and using 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, and we can said that at 5% of significance the proportion of chips that fail in the first 1000 hours of their use is not significantly less than 0.48.  

6 0
4 years ago
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