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konstantin123 [22]
3 years ago
6

The human body has a normal temperature of 98.6°F. Doctors will get worried if a sick patient has a temperature that varies from

the normal by more than 3°F. Create an absolute value inequality and solve it to determine what body temperatures would be considered unhealthy.
Mathematics
1 answer:
makvit [3.9K]3 years ago
6 0

Answer:

|T- 98.6| \geq 3

And in order to solve this we have two possibilities:

Solution 1

T -98.6 \leq -3

And solving for T we got:

T \leq 98.6- 3

T\leq 95.6

Solution 2

And the other options would be:

T -98.6 \geq 3

T \geq 101.6

Step-by-step explanation:

For this case we can define the variable os interest T as the real temperature and we know that if we are 3 F more than the value of 98.6 we will be unhealthy so we can set up the following equation:

|T- 98.6| \geq 3

And in order to solve this we have two possibilities:

Solution 1

T -98.6 \leq -3

And solving for T we got:

T \leq 98.6- 3

T\leq 95.6

Solution 2

And the other options would be:

T -98.6 \geq 3

T \geq 101.6

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Answer:

The test statistic is z = -2.11.

Step-by-step explanation:

Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Subtraction between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

Group 1: Sample of 35, mean of 1276, standard deviation of 347.

This means that:

\mu_1 = 1276, s_1 = \frac{347}{\sqrt{35}} = 58.6537

Group 2: Sample of 35, mean of 1439, standard deviation of 298.

This means that:

\mu_2 = 1439, s_2 = \frac{298}{\sqrt{35}} = 50.3712

Test if there is a difference in productivity level.

At the null hypothesis, we test that there is no difference, that is, the subtraction is 0. So

H_0: \mu_1 - \mu_2 = 0

At the alternate hypothesis, we test that there is difference, that is, the subtraction is different of 0. So

H_1: \mu_1 - \mu_2 \neq 0

The test statistic is:

z = \frac{X - \mu}{s}

In which X is the sample mean, \mu is the value tested at the null hypothesis and s is the standard error.

0 is tested at the null hypothesis:

This means that \mu = 0

From the two samples:

X = \mu_1 - \mu_2 = 1276 - 1439 = -163

s = \sqrt{s_1^2+s_2^2} = \sqrt{58.6537^2+50.3712^2} = 77.3144

Test statistic:

z = \frac{X - \mu}{s}

z = \frac{-163 - 0}{77.3144}

z = -2.11

The test statistic is z = -2.11.

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