Suppose the average weight for population of men is 178 pounds. You draw a random sample of 10 men and record the following weights:
150, 145, 180, 200, 175, 190, 142, 175, 240, 150.
Calculate the sampling error.
To calculate the sampling error, you need to find the difference between each individual weight in the sample and the average weight for the population.
First, calculate the sum of the sample weights:
150 + 145 + 180 + 200 + 175 + 190 + 142 + 175 + 240 + 150 = 1747
Next, divide the sum by the number of individuals in the sample to find the sample mean:
1747 / 10 = 174.7
Now, subtract the sample mean from the average weight for the population:
178 - 174.7 = 3.3
Therefore, the sampling error is 3.3 pounds.
To calculate the sampling error, we need to compare the sample mean with the population mean.
First, let's calculate the sample mean:
Sample mean = (150 + 145 + 180 + 200 + 175 + 190 + 142 + 175 + 240 + 150) / 10 = 1,747 / 10 = 174.7 pounds.
The population mean is given as 178 pounds.
Now, we can calculate the sampling error:
Sampling error = Sample mean - Population mean = 174.7 - 178 = -3.3 pounds.
Therefore, the sampling error is -3.3 pounds. The negative sign indicates that, on average, the sample weights are slightly lower than the population average.