Assume that weights of adult females are normally distributed with a mean of 79 kg and a standard deviation of 22 kg. What percentage of individual adult females have weights between 75 kg and 83 ​kg? If samples of 100 adult females are randomly selected and the mean weight is computed for each​ sample, what percentage of the sample means are between 75 kg and 83 ​kg?

Respuesta :

Answer:

14.28% of individual adult females have weights between 75 kg and 83 ​kg.

92.82% of the sample means are between 75 kg and 83 ​kg.

Step-by-step explanation:

The Central Limit Theorem estabilishes that, for a random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], a large sample size can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]\frac{\sigma}{\sqrt{n}}[/tex].

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this problem, we have that:

Assume that weights of adult females are normally distributed with a mean of 79 kg and a standard deviation of 22 kg. This means that [tex]\mu = 79, \sigma = 22[/tex].

What percentage of individual adult females have weights between 75 kg and 83 ​kg?

This percentage is the pvalue of Z when [tex]X = 83[/tex] subtracted by the pvalue of Z when [tex]X = 75[/tex]. So:

X = 83

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{83 - 79}{22}[/tex]

[tex]Z = 0.18[/tex]

[tex]Z = 0.18[/tex] has a pvalue of 0.5714.

X = 75

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{75- 79}{22}[/tex]

[tex]Z = -0.18[/tex]

[tex]Z = -0.18[/tex] has a pvalue of 0.4286.

This means that 0.5714-0.4286 = 0.1428 = 14.28% of individual adult females have weights between 75 kg and 83 ​kg.

If samples of 100 adult females are randomly selected and the mean weight is computed for each​ sample, what percentage of the sample means are between 75 kg and 83 ​kg?

Now we use the Central Limit THeorem, when [tex]n = 100[/tex]. So [tex]s = \frac{22}{\sqrt{100}} = 2.2.[/tex]

X = 83

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{83 - 79}{2.2}[/tex]

[tex]Z = 1.8[/tex]

[tex]Z = 1.8[/tex] has a pvalue of 0.9641.

X = 75

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{75-79}{2.2}[/tex]

[tex]Z = -1.8[/tex]

[tex]Z = -1.8[/tex] has a pvalue of 0.0359.

This means that 0.9641-0.0359 = 0.9282 = 92.82% of the sample means are between 75 kg and 83 ​kg.

93.12% of the sample means are between 75 kg and 83 ​kg

Z score

The z score is used to determine by how many standard deviations the raw score is above or below the mean. It is given by:

z = (x - μ)/(σ/√n)

where x is raw score, σ is standard deviation and μ is mean and n is sample size

μ = 79, σ = 22, n = 100

For x > 75:

z = (75 - 79)/(22/√100) = -1.82

For x < 83:

z = (83 - 79)/(22/√100) = 1.82

P(-1.82< z < 1.82) = P(z < 1.82) - P(z < -1.82) = 0.9656 - 0.0344 = 0.9312

93.12% of the sample means are between 75 kg and 83 ​kg

Find out more on Z score at: https://brainly.com/question/25638875