Minutes
126.53 127.27 130 130.35 130.4 130.58
130.87 131.18 131.98 132.55 133.28 133.42
133.43 133.55 133.65 134 134.37 134.62
134.73 135 135.95 136.12 136.17 136.23
136.28 137.7 137.83 137.93 138.18 138.25
138.43 138.67 139.13 139.72 140.25 140.38
140.4 140.42 140.5 141.27 141.3 141.85
141.95 142.72 143.15 143.33 143.4 143.78
143.9 143.95 144.13 144.32 144.47 144.8
145.05 145.18 145.83 146.48 146.92 147.28
148.07 148.23 148.43 148.67 149.08 149.47
149.62 149.92 150.12 150.43 151.72 152.58
153.53 155.1 159.02 161.13 Use the Sampling Distribution for a Mean option in StatKey to create a sampling distribution using samples of size n equals 10 from Table 1 showing the number of minutes to finish the marathon at the Olympics. Generate at least 1000 samples in your sampling distribution and give the standard error of the sample means.
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To generate a sampling distribution using StatKey, follow these steps:
1. Enter the given data into StatKey. In this case, the data is the number of minutes to finish the marathon at the Olympics.
2. Select the "Sampling Distribution for a Mean" option in StatKey. This option allows you to create a sampling distribution using samples of a specific size.
3. Specify the sample size (n) as 10, as stated in the question. This means that each sample in the sampling distribution will consist of 10 marathon finish times randomly selected from the given data.
4. Generate at least 1000 samples in your sampling distribution. This will provide enough samples to obtain a reliable estimate of the sampling distribution.
5. Once the sampling distribution is generated, find the standard error of the sample means. The standard error is a measure of the variability of the sample means in the sampling distribution. It can be calculated using the formula:
standard error = standard deviation / √n
In this case, the standard deviation can be obtained from the sampling distribution and n is 10 (the sample size).
By following these steps, you can obtain the sampling distribution with at least 1000 samples and calculate the standard error of the sample means.