Normal Distribution of Means

In summary, the biologist collected three samples of Chickadees in North Glenmore Park, with mean masses of 13.23 grams, 9.64 grams, and 11.14 grams respectively. The population of Chickadees in the park has a mean mass of 10.87 grams and a standard deviation of 1.89 grams. Assuming a normal distribution, the probability of obtaining samples with means between 9.64 and 13.23 grams, each consisting of 14 individuals, is 0.6347. The correct calculation takes into account the standard deviation of the means, rather than the population standard deviations.
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jmm
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Homework Statement



A biologist interested in the mass of Chickadees (Poecile atricapillus) in North Glenmore Park collects the 3 samples shown below:
Sample 1: 9 individuals with a mean mass of 13.23 grams
Sample 2: 16 individuals with a mean mass of 9.64 grams
Sample 3: 13 individuals with a mean mass of 11.14 grams

b. The population of Chickadees in North Glenmore Park has a mean mass of 10.87 grams and a standard deviation of 1.89 grams. Assuming the population is normally distributed, what is the probability of obtaining samples such as these, with means between 9.64 and 13.23 grams, if each sample were comprised of 14 individuals?

Homework Equations



z = (xbar - µ) / ∂

The Attempt at a Solution



So I think the probability would be P(xbar < 13.23) - P(xbar < 9.64). For xbar = 13.23, z=1.25 and p = 0.8925, for xbar = 9.64, z = -0.65 and p = 0.2578. So P(9.64 < xbar < 13.23) = 0.8925 - 0.2578 = 0.6347. Am I on the right track with this or am I completely off? I'm confused why they mention that each sample is composed of 14 individuals.

Thank you.
 
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  • #2
Never mind; I just figured out that I need to use the standard deviation of the means to calculate the z scores instead of the population standard deviations. Thanks anyways!
 

What is the normal distribution of means?

The normal distribution of means is a statistical concept that describes the distribution of a population's mean values. It follows a bell curve shape, with the majority of values falling near the average or mean, and fewer values falling towards the extremes.

What is the central limit theorem?

The central limit theorem is a statistical principle that states that as the sample size increases, the distribution of sample means will approach a normal distribution, regardless of the shape of the population distribution. This allows for the use of normal distribution to make inferences about a population based on a sample.

How is the normal distribution of means calculated?

The normal distribution of means is calculated using the mean and standard deviation of a population or sample. The mean represents the average value, while the standard deviation measures the spread of values around the mean. These values are used to determine the shape, center, and spread of the normal distribution.

What is the purpose of the normal distribution of means?

The normal distribution of means is used in statistical analysis to make inferences and predictions about a population based on a sample. It is also used to test hypotheses and make decisions about whether a sample is representative of a larger population.

What are the assumptions of the normal distribution of means?

The assumptions of the normal distribution of means include: 1) the sample or population is normally distributed, 2) the sample is random, 3) the observations within the sample are independent, and 4) the sample size is large enough. Violation of these assumptions can affect the validity of using the normal distribution of means in statistical analysis.

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