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Anon25 [30]
3 years ago
11

4. The following intervals were plausible population proportions for a given sample. Find the margin of error in each case.

Mathematics
1 answer:
Vedmedyk [2.9K]3 years ago
3 0

Answer: a. 0.15  b. 0.03 c. 0.055 d. 0.05

Step-by-step explanation:

For plausible intervals of population proportions , the margin of error is basically half of the difference between upper limit and lower limit.

a.  Interval =  From 0.35 to 0.65

Upper limit = 0.65

Lower limit = 0.35

Difference = Upper limit- Lower limit

= 0.65-0.35=0.30

Margin of error = (Difference)÷2  =(0.30)÷2=0.15

b. Interval =  From 0.72 to 0.78

Upper limit = 0.78

Lower limit = 0.72

Difference =  0.78-0.72 = 0.06

Margin of error  =(0.06)÷2=0.03

c. Interval =  From 0.84 to 0.95

Upper limit = 0.95

Lower limit = 0.84

Difference =0.95-0.84= 0.11

Margin of error = (0.11)÷2 = 0.055

d.Interval =  From 0.47 to 0.57

Upper limit =  0.57

Lower limit =  0.47

Difference = 0.57-0.47=0.10

Margin of error = (0.10)÷2=0.05

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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.

7 0
3 years ago
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