A researcher wants to study the spending habits of customers of a local shopping mall. The mall manager claims that the average spending per customer is $70, but the researcher believes that the average is less than $70. A simple random sample of 350 shoppers is obtained. The sample average is $65 and the sample SD is $27. Find the SE for the sample average.

To find the Standard Error (SE) for the sample average, you can use the formula:

SE = Standard Deviation / √(Sample Size)

Given that the sample average is $65 (which we assume is the estimated population mean), and the sample standard deviation is $27, and the sample size is 350, we can calculate the SE as follows:

SE = 27 / √(350)

Now let's calculate it:

SE = 27 / √(350)
≈ 1.44666

Therefore, the Standard Error (SE) for the sample average is approximately $1.447.

To find the standard error (SE) for the sample average, you can use the following formula:

SE = sample standard deviation / square root of the sample size

In this case, the sample standard deviation (s) is given as $27, and the sample size (n) is 350. Plugging these values into the formula, we get:

SE = 27 / √350

To compute the value, you should:

1. Take the square root of the sample size, which is √350 ≈ 18.708.

2. Divide the sample standard deviation by the square root of the sample size: 27 / 18.708 ≈ 1.443.

Therefore, the standard error for the sample average is approximately $1.443.