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Munchie capture-recapture Your class can use the capture-recapture method described in the previous exercise to estimate the number of goldfish in a bag of Cheddar Goldfish. Pour the Cheddar Goldfish into a paper bag, which represents the pond. Sample 10 of them. For this initial sample, use Pretzel Goldfish to replace them, to represent the tagged fish. Then select a second sample and derive an estimate for \(N,\) the number of Cheddar Goldfish in the original bag. See how close your estimate comes to the actual number of fish in the bag. (Your teacher will count the population of Cheddar Goldfish in the bag before beginning the sampling.) If the estimate is not close, what could be responsible, and what would this reflect as difficulties in a real-life application such as sampling a wildlife population?

Short Answer

Expert verified
Capture 10 Goldfish, replace with Pretzels, recapture, and use the formula \( N = \frac{M \times n}{m} \) to estimate population.

Step by step solution

01

Understand the Capture-Recapture Method

Capture-recapture is a method used to estimate the size of a population. You first capture a sample of individuals from a population, mark them, and release them back into the population. After allowing some time for the marked individuals to mix with the unmarked ones, a second sample is captured, and the number of marked individuals within this sample is used to estimate the total population.
02

Initial Capture and Tagging

In this exercise, pull out 10 Cheddar Goldfish from the "pond" (bag). Replace these 10 with Pretzel Goldfish, representing the tagged (or marked) individuals. This initial sample is your tagged sample, which aids in estimating the total number of Cheddar Goldfish.
03

Second Sampling

Once the Pretzel Goldfish have mixed with the Cheddar Goldfish, draw another sample, the same size as before or different. Record how many Pretzel Goldfish (tagged) are in this second sample.
04

Use the Capture-Recapture Formula

Apply the formula for capture-recapture:\[N = \frac{M \times n}{m}\]Where:- \( N \) is the total population size (number of Cheddar Goldfish in the original bag).- \( M \) is the number of marked individuals from the first sample (Pretzel Goldfish), 10 in this case.- \( n \) is the total number of individuals in the second sample.- \( m \) is the number of marked individuals in the second sample (Pretzel Goldfish).
05

Calculate and Analyze Results

Substitute the values obtained from your second sample into the formula to find \( N \). Compare your estimate to the actual total counted by the teacher. Analyze if your estimate is close to the actual number. If not, consider reasons such as insufficient mixing time, biased sample selection, or small sample sizes affecting the estimation's accuracy.
06

Reflect on Real-Life Application Challenges

Discuss potential issues that could arise when using this method in real-life scenarios, like estimating wildlife populations. Reflect on factors like animal movement, observer bias, or environmental conditions, which could affect the mixing of the population and the accuracy of the estimate.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Population estimation
The capture-recapture method is a statistical tool used for estimating the size of a population, which is hard to count directly. This method makes use of sampling techniques to provide an approximation, rather than an exact count. The primary goal is to estimate the total number of individuals in a population from just two sampling efforts.
In the exercise, the task was to estimate the number of Cheddar Goldfish in a bag. By initially capturing some goldfish, marking them with Pretzel Goldfish, and then sampling again, we derive an estimate for the full population using the capture-recapture formula. The estimation involves counting how many marked (Pretzel) fish appear in the second sample, which helps infer the population size.
This process is pivotal in ecology, helping scientists estimate populations in wildlife studies. It allows for population size assessments without needing to count every individual, which might be impractical in complex, natural environments.
Statistical sampling
Statistical sampling is at the core of the capture-recapture method. This technique entails selecting a subset of individuals from a population to understand characteristics of the whole group. It turns an infeasible counting task into a manageable estimation problem.
Sampling occurs in two stages in this context. The first sample is used to mark individuals—here, Pretzel Goldfish replace the sampled Cheddar Goldfish. This initial sampling and "marking" stage is vital as it lays the groundwork for the second capture phase.
When sampling a second time, we seek to determine how many tagged individuals resurface. This provides data to use in our formula to estimate the total population. Crucially, proper statistical sampling considers unbiased and random selection to ensure accurate and reliable results. Errors in sampling could lead to faulty conclusions, emphasizing the importance of careful experimental planning.
Experimental design
Designing an experiment using the capture-recapture model involves careful planning to ensure accurate results. The setup for marking and resampling must minimize biases and errors that could distort estimates.
The experimental procedure in this exercise involved substituting captured Cheddar Goldfish with Pretzel Goldfish as a marking method. Mixing these marked individuals thoroughly with the rest is crucial. If the marked individuals have not mixed adequately, the second sample might not accurately represent how many originally marked individuals are present in the total population.
In wildlife contexts, experimental design must also address the mobility of the animals, their behavior, and environmental conditions, all of which could affect mixing and, thereby, estimation accuracy. Design considerations like timing of sampling, method of marking (e.g., tags, paint), and duration between samplings are critical parameters. Each of these elements can significantly impact how well the experimental findings reflect the actual population size.

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Most popular questions from this chapter

Mean family size You'd like to estimate the mean size of families in your community. Explain why you'll tend to get a smaller sample mean if you sample \(n\) families than if you sample \(n\) individuals (asking them to report their family size). (Hint: When you sample individuals, explain why you are more likely to sample a large family than a small family. To think of this, it may help to consider the case \(n=1\) with a population of two families, one with 10 people and one with only 2 people.)

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Activity: Sampling the states This activity illustrates how sampling bias can result when you use a nonrandom sample, even if you attempt to make it representative: You are in a geography class, discussing center and variability for several characteristics of the states in the contiguous United States. A particular value of center is the mean area of the states. A map and a list of the states with their areas (in square miles) are shown in the figure and table that follow. Area for a state includes dry land and permanent inland water surface. Although we could use these data to calculate the actual mean area, let's explore how well sampling perfoms in estimating the mean area by sampling five states and finding the sample mean. a. The most convenient sampling design is to use our eyes to pick five states from the map that we think have areas representative of all the states. Do this, picking five states that you believe have areas representative of the actual mean area of the states. Compute their sample mean area. b. Collect the sample means for all class members. Construct a dot plot of these means. Describe the distribution of sample means. Note the shape, center, and variability of the distribution. c. Another possible sampling design is simple random sampling. Randomly select five states (using an app or computer program) and compute the sample mean area. d. Collect the sample means from part c of all class members. Construct a dot plot of the sample means using the same horizontal scale as in part b. Describe this distribution of sample means. Note the shape, center, and variability of the distribution. e. The true mean total land area for the 48 states can be calculated from the accompanying table by dividing the total at the bottom of the table by \(48 .\) Which sampling method, using your eyes or using random selection, tended to be better at estimating the true population mean? Which method seems to be less biased? Explain. f. Write a short summary comparing the two distributions of sample means. $$ \begin{array}{lr} \hline \ {\text { Areas of the } 48 \text { States in the Continental U.S. }} \\\ \hline \text { State } & \text { Area (square miles) } \\ \hline \text { Alabama } & 52,419 \\ \text { Arizona } & 113,998 \\ \text { Arkansas } & 53,179 \\ \text { California } & 163,696 \\ \text { Colorado } & 104,094 \\ \text { Connecticut } & 5,543 \\ \text { Delaware } & 2,489 \\ \text { Florida } & 65,755 \\ \text { Georgia } & 59,425 \\ \text { Idaho } & 83,570 \\ \text { Illinois } & 57,914 \\ \text { Indiana } & 36,418 \\ \text { Iowa } & 56,272 \\ \text { Kansas } & 82,277 \\ \text { Kentucky } & 40,409 \\ \text { Louisiana } & 51,840 \\ \text { Maine } & 35,385 \\ \text { Maryland } & 12,407 \\ \text { Massachusetts } & 10,555 \\ \text { Michigan } & 96,716 \\ \text { Minnesota } & 86,939 \\ \text { Mississippi } & 48,430 \\ \text { Missouri } & 69,704 \\ \text { Montana } & 147,042 \\ \text { Nebraska } & 77,354 \\ \text { Nevada } & 110,561 \\ \text { New Hampshire } & 9,350 \\ \text { New Jersey } & 8,721 \\ \text { New Mexico } & 121,589 \\ \text { New York } & 54,556 \\ \text { North Carolina } & 53,819 \\ \text { North Dakota } & 70,700 \\ \text { Ohio } & 44,825 \\ \text { Oklahoma } & 69,898 \\ \text { Oregon } & 98,381 \\ \text { Pennsylvania } & 46,055 \\ \text { Rhode Island } & 1,545 \\ \text { South Carolina } & 32,020 \\ \text { South Dakota } & 77,116 \\ \text { Tennessee } & 42,143 \\ \text { Texas } & 268,581 \\ \text { Utah } & 84,899 \\ \text { Vermont } & 9,614 \\ \text { Virginia } & 42,774 \\ \text { Washington } & 71,300 \\ \text { West Virginia } & 24,230 \\ \text { Wisconsin } & 65,498 \\ \text { Wyoming } & 97,814 \\ \text { U.S. TOTAL } & \mathbf{3 , 1 1 9 , 8 1 9} \\ \hline \end{array} $$

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