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Burka [1]
3 years ago
15

One piece of paper is 13.45 cm long. Another piece of paper is 15.125 cm long. What is the total length of these two pieces of p

aper? if you could tell me how to figger it out that would help a lot thx
Mathematics
1 answer:
maksim [4K]3 years ago
8 0
You find the total of two numbers by adding them.
  13.450 + 15.125 = 28.575

The total length of the two sheets of paper is 28.575 cm.
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A genetic experiment involving peas yielded one sample of offspring consisting of 409 green peas and 171 yellow peas. Use a 0.05
grigory [225]
The usual expectation for this kind of experiment is that the peas would yield green and yellow peas in a 3:1 ratio, or 75% green to 25% yellow. So your null hypothesis is that the proportion of yellow peas is p=0.25.

You're testing the claim that 26% of the offspring will be yellow, which means the alternative hypothesis is that the proportion of yellow peas is actually 0.26, or more generally that the expected proportion is greater than 0.25, or p>0.25.

The test statistic in this case will be

Z=\dfrac{\hat p-p_0}{\sqrt{\dfrac{p_0(1-p_0)}n}}

where p_0 is the proportion assumed under the null hypothesis, \hat p is the measured proportion, and n is the sample size. You have p_0=0.25, \hat p=\dfrac{171}{171+409}\approx0.29, and n=409+171=580, so the test statistic is

Z=\dfrac{0.29-0.25}{\sqrt{\dfrac{0.25\times0.75}{580}}}\approx2.2247

Because you're testing p>p_0, this is a right-tailed test, so the P-value is

\mathbb P(Z>2.2247)\approx0.0131

The critical value for a right-tail test at a 0.05 significance level is Z_\alpha\approx1.6449, which means the rejection region is any test statistic that is larger than this critical value. Since Z>Z_\alpha in this case, we reject the null hypothesis.

So the conclusion for this test is that the sample proportion is indeed statistically significantly different from the proportion suggested by the null hypothesis.
8 0
3 years ago
Read 2 more answers
Which expression is equivalent to 91+39 ?
KIM [24]

Answer:

130

Step-by-step explanation:

i think

5 0
3 years ago
Find the 7th term of (x+y)^8
Rzqust [24]
The answer is a , solve everything out and work it out you will see how i got it
8 0
3 years ago
-2x+4y= 12 3x+7y= 18 last one greatly appreciated
LenaWriter [7]

Value of x is \frac{-6}{13}\\ and y is \frac{36}{13}

Solution set is (\frac{-6}{13}\\, \frac{36}{13})

Step-by-step explanation:

We need to solve the system of equations given.

-2x+4y=12\\3x+7y= 18

Solving

Let:

-2x+4y=12\,\,eq(1)\\3x+7y=18\,\,eq(2)

Multiply eq(1) by 3 and eq(2) by 2 and add both

-6x+12y=36\\6x+14y=36\\-------\\26y=72\\y=\frac{72}{26}\\y=\frac{36}{13}

Putting value of y in equation 1

-2x+4y=12\\-2x+4(\frac{36}{13})=12\\-2x+\frac{144}{13}=12\\-2x=12-\frac{144}{13}\\-2x=\frac{12*13-144}{13}\\-2x=\frac{12}{13}\\x=\frac{-6}{13}\\

So, value of x is \frac{-6}{13}\\ and y is \frac{36}{13}

Solution set is (\frac{-6}{13}\\, \frac{36}{13})

Keywords: System of equations

Learn more about system of equations at:

  • brainly.com/question/9045597
  • brainly.com/question/3739260
  • brainly.com/question/13168205

#learnwithBrainly

7 0
3 years ago
The population of scores on a nationally standardized test forms a normal distribution with μ = 300 and σ = 50. If you take a ra
madreJ [45]

Answer:

P(\bar X

And using a calculator, excel or the normal standard table we have that:

P(Z

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the scores of a population, and for this case we know the distribution for X is given by:

X \sim N(300,50)  

Where \mu=300 and \sigma=50

Since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

We can find the individual probability like this:

P(\bar X

And using a calculator, excel or the normal standard table we have that:

P(Z

4 0
3 years ago
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