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Homser Lake, Oregon, has an Atlantic salmon catch-and-release program that has been very successful. The average fisherman's catch has been \( \mu=8.4 \). Atlantic salmon per day. Suppose that a new quota system restricting the number of fishermen has been put into effect this season. A random sample of fishermen gave the following catches per day: \( 11,6,11,11,5,2,1,7,7,8,6,2,12,13 \) Assuming the catch per day has an approximately normal distribution, does the sample indicate at a 0.1 level of significance that the population average catch per day is now different from 8.4 ? A) Use a calculator with the "Stats" feature to find \( \overline{\bar{x}} \) and \( s \). (Round your answer to 2 decimal places). \[ \bar{x}=7.29 \] \[ s=3.93 \] B) State the Null and Alternate hypotheses. \( H_{0}: \mu=8.4 ; H_{1}: \mu>8.4 \) \( H_{0}: \mu>8.4 ; H_{1}: \mu=8.4 \) \( H_{0}{ }^{-} \mu \neq 8.4: H_{1}: \mu=8.4 \) \( H_{0}^{*}{ }^{*} \mu=8.4: H_{1}: \mu<8.4 \) ० \( H_{0}: \mu=8.4 ; H_{1}: \mu \neq 8.4 \) C) Is this a (left-tail, right-tail, one-tail, two-tail) test? one-tail two-tail left-tail right-tail D) Accurate to 3 decimal places, find the \( t^{*} \) value of the sample. \[ -1.018 \times \] E) Find the degree of freedom of the sample. \[ 13 \] F) Accurate to 4 decimal places, what's the p-value of the sample? \( \square \)

Ask by Martinez Pierce. in the United States
Mar 09,2025

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Answer

**A) Sample Mean and Standard Deviation** \[ \bar{x} = 7.29, \quad s = 3.93 \] **B) Hypotheses** \[ H_0: \mu = 8.4, \quad H_1: \mu \neq 8.4 \] **C) Test Type** Two-tail test **D) Test Statistic \(t^*\)** \[ t^* \approx -1.06 \] **E) Degrees of Freedom** \[ df = 13 \] **F) p-value** \[ p \approx 0.3110 \]

Solution

**A) Calculation of the Sample Mean and Standard Deviation** The sample mean and standard deviation are given by \[ \bar{x}=7.29 \quad \text{and} \quad s=3.93. \] **B) Statement of Null and Alternative Hypotheses** Since we are testing whether the population mean has changed from \(8.4\) (i.e. “different than” \(8.4\)), the hypotheses are \[ H_0: \mu = 8.4 \quad \text{and} \quad H_1: \mu \neq 8.4. \] **C) Type of Test** Because the alternative hypothesis is “\(\mu \neq 8.4\),” this is a **two-tail** test. **D) Computation of the Test Statistic \(t^*\)** The test statistic is given by \[ t^* = \frac{\bar{x} - \mu_0}{\dfrac{s}{\sqrt{n}}}, \] where \(\bar{x}=7.29\), \(\mu_0 = 8.4\), \( s=3.93 \), and \( n = 14 \). 1. Compute the numerator: \[ \bar{x} - \mu_0 = 7.29 - 8.4 = -1.11. \] 2. Compute the denominator: \[ \frac{s}{\sqrt{n}} = \frac{3.93}{\sqrt{14}} \approx \frac{3.93}{3.7417} \approx 1.05. \] 3. Therefore, \[ t^* \approx \frac{-1.11}{1.05} \approx -1.057. \] Rounded to three decimal places, \[ t^* \approx -1.057. \] **E) Degrees of Freedom** Degrees of freedom is given by \[ df = n - 1 = 14 - 1 = 13. \] **F) Calculation of the p-value** Since this is a two-tail test, the p-value is \[ \text{p-value} = 2\;P\left(T \le t^*\right) \] with \(df = 13\) and \(t^* \approx -1.057\). Using a \(t\)-distribution calculator or table, we find that the one-tail probability corresponding to \(t^*=-1.057\) (or equivalently, \(|t^*|=1.057\)) for \(13\) degrees of freedom is approximately \(0.1555\). Thus, \[ \text{p-value} \approx 2\times 0.1555 = 0.3110. \] Rounded to four decimal places, \[ \text{p-value} \approx 0.3110. \]

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The catch-and-release program for Atlantic salmon at Homser Lake reflects a long-standing commitment to sustainable fishing. Over the years, this initiative has not only helped restore the salmon population but has also provided a unique opportunity for anglers to engage in conservation. Such programs often foster a community of responsible fishers who understand the importance of maintaining healthy aquatic ecosystems while enjoying their sport! Additionally, many regions have turned to scientific studies to gather data on fisheries management. By analyzing catch data, researchers can refine quotas and ensure a balance between recreational fishing and conservation efforts. This blending of science and outdoor fun illustrates how effective regulatory measures can lead to thriving fish populations and happy anglers!

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