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kap26 [50]
3 years ago
15

(a) A yoga instructor collected student data. She found that students who had less sleep did not tend to burn more or fewer calo

ries
during class. What can she conclude?
There is no correlation between amount of sleep and number of calories burned.
There is a correlation between amount of sleep and number of calories burned. There may or may not be causation. Further studies would
have to be done to determine this.
There is a correlation between amount of sleep and number of calories burned. There is probably also causation. This is because there is likely
an increase in the number of calories burned with an increase in the amount of sleep.
Mathematics
1 answer:
beks73 [17]3 years ago
7 0

Answer:

The answer is ( A) -There is no correlation between amount of sleep and number of calories burned

Step-by-step explanation:

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Would like an answer for this question. Which represents 7(45) using the distributive property to simplify? SELECT THE TWO THAT
makkiz [27]

Answer:

7(45)=7(40)+7(5)

Step-by-step explanation:

We need to represent 7(45) using the distributive property to simplify.

We can write 45 as 40+5

So it becomes,

7(45) = 7(40+5)

Distributive property is : a(b+c)=ab+ac

a=7, b = 40 and c = 5

7(40+5)=7(40)+7(5)

So, the correct option is (4).

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Answer:

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Step-by-step explanation:

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3 years ago
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4 years ago
Brainliest + 20 pts to whoever helps pls!!
Blizzard [7]

Answer:

Correct option is (a). 60.391 and 101.879; because the test statistic is in a critical region, the test rejects the null hypothesis.

Step-by-step explanation:

A Chi-square test for population variance is used to perform this test.

The standard deviation is, 2.0 minutes.

Then the variance is, 4.0 minutes.

The hypothesis for this test is:

<em>H₀</em>: The population variance of all commute times is equal to 4.0 minutes, i.e. <em>σ² </em>= 4.

<em>Hₐ</em>: The population variance of all commute times is not equal to 4.0 minutes, i.e. <em>σ² </em>≠ 4.

The test statistic is:

\chi^{2}_{calc.}=\frac{(n-1)s^{2}}{\sigma^{2}}

The critical region of this test is defined as:

Reject <em>H₀</em> if \chi^{2}_{calc.} or \chi^{2}_{calc.}>\chi^{2}_{(1-\alpha /2), (n-1)}.

The degrees of freedom is:

n-1=81-1=80

Compute the critical from a Chi-square table.

\chi^{2}_{\alpha /2, (n-1)}=\chi^{2}_{0.05, 80}=101.879\\\chi^{2}_{(1-\alpha /2), (n-1)}=\chi^{2}_{0.95, 80}=60.391\\

The test statistic value is, \chi^{2}_{calc.}=105.8.

\chi^{2}_{calc.}=105.8 > \chi^{2}_{0.05, 80}=101.879

The null hypothesis is rejected because the test statistic is in the critical region.

Thus, the correct option is (a).

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