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Weights of golden retriever dogs are normally distributed. Samples of weights of golden retriever dogs, each of size \( n=15 \), are randomly collected and the sample means are found. Is it correct to conclude that the sample means cannot be treated as being from a normal distribution because the sample size is too small? Explain. Choose the correct answer below. A. Yes; the sample size must be over 30 for the sample means to be normally distributed. B. No; the samples are collected randomly, so the sample means will be normally distributed for any sample size. C. No; the original population is normally distributed, so the sample means will be normally distributed for any sample size. D. No; as long as more than 30 samples are collected, the sample means will be normally distributed.

Ask by Joseph Gough. in the United States
Mar 09,2025

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The sample means are normally distributed because the original population of dog weights is normally distributed, regardless of the sample size.

Solución

Since the population of weights is normally distributed, the distribution of the sample means is also normal regardless of the sample size \( n \), even when \( n = 15 \). Here’s the reasoning step by step: - The weights of the golden retriever dogs are normally distributed. - When you take a sample of size \( n \) from a normal population, the sample mean is normally distributed regardless of the size \( n \). - This is a property of the normal distribution: any linear combination (including the average) of normally distributed variables is also normally distributed. Thus, even though the sample size is less than 30, the sample means are normally distributed. The correct answer is: C. No; the original population is normally distributed, so the sample means will be normally distributed for any sample size.

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Bonus Knowledge

C. No; the original population is normally distributed, so the sample means will be normally distributed for any sample size. Since the weights of golden retriever dogs follow a normal distribution, the sample means will also be normally distributed, regardless of the sample size. This characteristic stems from the Central Limit Theorem, but in this case, since we already know the parent population is normal, the sample means will remain normal even with smaller sample sizes, like \( n=15 \). So, you can feel confident in your conclusions! Now, let’s keep things dynamic! Did you know that during the 19th century, golden retrievers were bred primarily for retrieving game during hunting? This unique heritage highlights their intelligence and trainability, making them exceptional companions—not just for hunters but for families around the world today. Plus, golden retrievers are famous for their friendly demeanor!

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Question 12(Mulliple Choice Warth 5 points) \[ (04.06 \mathrm{HC}) \] A researcher wants to test the claim that the proportion of juniors who watch television regularly is greater than the proportion of seniors who watch television regularly She finds that 56 of 70 randomly selected juniors and 47 of 85 randomly selected seniors report watching television regularly. Construct \( 95 \% \) confidence intervals for each population proportion. Which of the statemente gives the correct outcome of the research or's tert of the dalim? The \( 95 \% \) confidence interval for juniors is (706, 894), and the \( 95 \% \) confidence interval for seniors is ( 447,659 ). Since the intervals overlap, there is not enough evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is (721, 879), and the \( 95 \% \) confidence interval for seniors is (464, 642). Since the interval for juniors is higher than the interval for seniors, there is evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is ( 706,894 ), and the \( 95 \% \) confidence interval for seniors is ( 447,659 ). Since the interval for juniors is higher than the interval for seniors, there is evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors. The \( 95 \% \) confidence interval for juniors is ( \( 721, .879 \) ), and the \( 95 \% \) confidence interval for seniors is (464, 642). Since the intervals overlap, there is not enough evidence to say the proportion of juniors who watch television regularly may be higher than that of seniors.

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