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marin [14]
3 years ago
14

​Cosella is conducting an experiment where she assesses how quickly teenagers can run a 100-meter race after consuming specific

amounts of caffeine. She divides her sample up into three groups. Group 1 receives a glass of water with no caffeine added. Group 2 receives a glass of water with an amount of caffeine equivalent to that in one cup of coffee. Group 3 receives a glass of water with an amount of caffeine equivalent to that in two cups of coffee. Each participant is then timed as they run the course. In this study, the independent variable is
a. the previous running experience of each participant
b. the teenagers who are being studied
c. the time it takes to run the 100-meter race
d. the amount of caffeine being ingested
Mathematics
1 answer:
qwelly [4]3 years ago
4 0

Answer:

c. the time it takes to run the 100-meter race

Step-by-step explanation:

An independent variable is the variable which is not being controlled and it does not depend on the other variables. This is the variable which is being studied/measured in the experiment.

Option a. The previous running experience is not being considered and is not a variable under study in this case. So this is not the answer.

Option b. The teenagers who are being studied constitute the sample. These are not the variables.

Option c. Time is the independent variable, as it is being measured during the experiment and the conclusion is being drawn based on it.

Option d. Amount of caffeine is being decided by Cosella and is therefore not the independent variable.

Therefore, the correct answer is option c

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Step-by-step explanation:

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The heights of North American women are normally distributed with a mean of 64 inches and a standard deviation of 2inches.a. Wha
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Answer:

a)P(X>66)=P(Z>1)=1-P(Z

b)P(\bar X >66)=P(Z>2)=1-P(Z

c) P(\bar X >66)=P(Z>10)=1-P(Z

Step-by-step explanation:

1) 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".  

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

2) Part a

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

X \sim N(64,2)  

Where \mu=64 and \sigma=2

We are interested on this probability

P(X>66)

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(X>66)=P(\frac{X-\mu}{\sigma}>\frac{66-\mu}{\sigma})=P(Z>\frac{66-64}{2})=P(Z>1)

And we can find this probability on this way:

P(Z>1)=1-P(Z

3) Part b

From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

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

P(\bar X >66)=P(Z>\frac{66-64}{\frac{2}{\sqrt{4}}}=2)

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

P(Z>2)=1-P(Z

4) Part c

P(\bar X >66)=P(Z>\frac{66-64}{\frac{2}{\sqrt{100}}}=10)

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

P(Z>10)=1-P(Z

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I hope this helps and have a wonderful day filled with joy!!


<3
8 0
4 years ago
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