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. need to understand how to solve thanks
To create a sampling distribution using the samples of size 10, you can follow these steps:
1. Input the given data into StatKey. Each marathon finishing time should be entered as a separate observation or data point.
- 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
2. Locate and select the option for "Sampling Distribution for a Mean" in StatKey. This option will calculate the sample means for each sample of size 10.
3. Specify the number of samples you want to generate. In this case, you should generate at least 1000 samples.
4. Once the sampling distribution is generated, the standard error of the sample means can be obtained from the output. The standard error is a measure of the variability or spread of the sample means.
By following these steps, you will obtain the sampling distribution with the standard error of the sample means using the given data.
To solve this problem, you can use the Sampling Distribution for a Mean option in StatKey. This tool will allow you to create a sampling distribution using samples of size n equals 10 from the given data and calculate the standard error of the sample means.
Here are the steps to follow:
1. Open StatKey and select the "Sampling Distribution for a Mean" option.
2. Enter the data provided in Table 1, which represents the number of minutes to finish the marathon at the Olympics.
3. Set the sample size (n) to 10.
4. Choose the number of samples you would like to generate. In this case, it is recommended to generate at least 1000 samples for a reliable sampling distribution.
5. Click on the "Generate Samples" or similar button to create the sampling distribution.
6. Once the sampling distribution is generated, you will find various statistics, including the standard error of the sample means. This value represents the standard deviation of the sample means and estimates the variability of the sample means around the population mean.
By following these steps, you will be able to obtain the standard error of the sample means using the Sampling Distribution for a Mean option in StatKey based on the given data.