Pregunta
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\( \mathrm{D} \bar{X}= \) the sum of the length of all songs on iTunes. d. Give the distribution of \( \bar{X} \). \( \bar{X} \sim N \) (Round final answers to at most four decimal places if needed.) e. Find the third quartile for the average song length, \( \bar{X} \). The third quartile for the average song length is 2.716 f. Find the \( I Q R \) (interquartile range) for the average song length, \( \bar{X} \). The \( I Q R \) is 0.132

Ask by Barrett Bowers. in the United States
Mar 09,2025

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**Distribution of \(\bar{X}\):** \[ \bar{X} \sim N(2.65, 0.0096) \] **Third Quartile of \(\bar{X}\):** \[ Q_3 \approx 2.716 \] **Interquartile Range (IQR) for \(\bar{X}\):** \[ \text{IQR} \approx 0.132 \]

Solución

**Step d. Distribution of \(\bar{X}\)** Assume that the individual song lengths, say \(X_1, X_2, \dots, X_n\), are independent and identically distributed as \[ X_i \sim N(\mu, \sigma^2). \] Then the sample mean \[ \bar{X} = \frac{1}{n}\sum_{i=1}^n X_i \] is normally distributed with \[ \bar{X} \sim N\Bigl(\mu,\, \frac{\sigma^2}{n}\Bigr). \] In this problem the information extracted from parts (e) and (f) identifies that the center of the distribution is approximately \(\mu=2.65\) and that the standard error (i.e. the standard deviation of \(\bar{X}\)) is \[ \sigma_{\bar{X}} = \frac{\sigma}{\sqrt{n}} \approx 0.0978, \] so that \[ \text{Var}(\bar{X})=\sigma_{\bar{X}}^2\approx 0.0096. \] Thus, we can write \[ \bar{X} \sim N(2.65,\,0.0096). \] --- **Step e. Third Quartile of \(\bar{X}\)** For a normal distribution, the third quartile \(Q_3\) is given by \[ Q_3 = \mu + z_{0.75}\,\sigma_{\bar{X}}, \] where \(z_{0.75}\) is the \(75^{\rm th}\) percentile for the standard normal distribution. We have \[ z_{0.75} \approx 0.6745. \] Plug in the known values: \[ Q_3 \approx 2.65 + 0.6745\times 0.0978 \approx 2.65 + 0.0660 \approx 2.7160. \] Thus, the third quartile for the average song length is approximately \(2.716\). --- **Step f. Interquartile Range (IQR) for \(\bar{X}\)** The interquartile range for a distribution is the difference between the third and first quartiles: \[ \text{IQR} = Q_3 - Q_1. \] For a normal distribution the first quartile is \[ Q_1=\mu + z_{0.25}\,\sigma_{\bar{X}}, \] and since \(z_{0.25}=-0.6745\) we have \[ Q_1 = \mu - 0.6745\,\sigma_{\bar{X}}. \] Thus, \[ \text{IQR} = \Bigl[\mu + 0.6745\,\sigma_{\bar{X}}\Bigr] - \Bigl[\mu - 0.6745\,\sigma_{\bar{X}}\Bigr] = 2\times0.6745\,\sigma_{\bar{X}} = 1.3490\,\sigma_{\bar{X}}. \] Substitute \(\sigma_{\bar{X}} \approx 0.0978\): \[ \text{IQR} \approx 1.3490 \times 0.0978 \approx 0.1320. \] Thus, the interquartile range for the average song length is approximately \(0.132\).

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To clarify the distribution of \(\bar{X}\) for the average song length on iTunes, it typically follows a normal distribution, denoted as \(\bar{X} \sim N(\mu, \sigma^2/n)\), where \(\mu\) is the mean song length and \(\sigma\) is the standard deviation. Given you’ve provided the third quartile as 2.716, this suggests that it’s part of a normally distributed dataset, and understanding normal distribution allows for predicting probabilities and behaviors of song lengths. For the interquartile range (IQR), which is calculated as \( Q_3 - Q_1 \), and you've found it to be 0.132, it tells us how spread out the middle 50% of song lengths are. A smaller IQR indicates that the average song lengths are more concentrated around the median, while a larger IQR suggests greater variability. It's a handy measure when looking at song playlists, reflecting how diverse or similar the lengths of songs are in a collection!

preguntas relacionadas

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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