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AleksAgata [21]
3 years ago
14

If it rains, then the game will be canceled Hypothesis: Conclusion:

Mathematics
1 answer:
yarga [219]3 years ago
6 0
<h3>Answers:</h3>

Hypothesis = It rains

Conclusion = The game is canceled

=====================================================

Explanation:

The general format for a conditional is "If P, then Q".

P is the hypothesis and Q is the conclusion. They are placeholders.

In this case

  • P = It rains
  • Q = The game is canceled

Some textbooks will write P \to Q to indicate "if P, then Q"

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Step-by-step explanation:

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Part (1)

n is some positive integer. Let's say for now that n is even. So n = 2k, for some integer k

This means n-1 = 2k-1 is odd since subtracting 1 from an even number leads to an odd number.

Now multiply n with n-1 to get

n(n-1) = 2k(2k-1) = 2m

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The result 2m is even showing that n(n-1) is even

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Let's say that n is odd this time. That means n = 2k+1 for some integer k

And also n-1 = 2k+1-1 = 2k showing n-1 is even

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where m = k(2k+1) is an integer

We've shown that n(n-1) is even here as well.

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So overall, n(n-1) is even regardless if n is even or if n is odd.

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Part (2)

n is some positive integer

2n is always even since 2 is a factor of 2n

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Another way to see how 2n+1 is odd is to divide 2n+1 over 2 and you'll find that we get (2n+1)/2 = 2n/2+1/2 = n+0.5

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6 0
3 years ago
Iron deficiency anemia is an important nutritional health problem in the U.S. A dietary assessment was performed on 51 boys 9-11
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Answer:

a) Null hypothesis:\mu = 14.44    

Alternative hypothesis:\mu \neq 14.44    

b) t=\frac{12.50-14.44}{\frac{4.75}{\sqrt{51}}}=-2.917    

The degrees of freedom are given by:

df =n-1= 51-1=50

Now we can calculate the p value taking in count the alternative hypothesis

p_v =2*P(t_{50}

Since the p value is lower than the significance \alpha=0.05 we have enough evidence to reject the null hypothesis and the true mean is significantly different from 14.44

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Step-by-step explanation:

Information given

\bar X=12.50 represent the mean for the daily iron intake

s=4.75 represent the sample deviation

n=51 sample size    

\mu_o =14.44 represent the reference value  

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

t would represent the statistic

p_v represent the p value for the test

Part a

We want to test if the mean iron intake among the low-income group is different from that of the general population, the system of hypothesis would be:    

Null hypothesis:\mu = 14.44    

Alternative hypothesis:\mu \neq 14.44  

Part b  

Since we don't know the population deviation the statistic would be given by:

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

Replacing the info we got

t=\frac{12.50-14.44}{\frac{4.75}{\sqrt{51}}}=-2.917    

The degrees of freedom are given by:

df =n-1= 51-1=50

Now we can calculate the p value taking in count the alternative hypothesis

p_v =2*P(t_{50}

Since the p value is lower than the significance \alpha=0.05 we have enough evidence to reject the null hypothesis and the true mean is significantly different from 14.44

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\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}

For the 95% confidence interval we can find the critical value in a t distribution with 50 degrees of freedom and we got:

t_{\alpha/2}= 2.01

And replacing we got:

12.50 -2.01 \frac{4.75}{\sqrt{51}}= 11.163

12.50 +2.01 \frac{4.75}{\sqrt{51}}= 13.837

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