
To find how many defective watches we would expect out of a total of 10,500, we need to use proportion.
Proportion of defective watches in the sample = 3/400 = 0.0075
We can use this proportion to estimate the number of defective watches in the entire population:
Expected number of defective watches = Proportion of defective watches x Total number of watches
Expected number of defective watches = 0.0075 x 10,500
Expected number of defective watches = 79
Therefore, based on the sample data, we would expect approximately 79 out of 10,500 watches to be defective.

that isnt correct

I apologize for the mistake in my previous response. Here is the correct solution:
Proportion of defective watches in the sample = 3/400 = 0.0075
We can use this proportion to estimate the number of defective watches in the entire population:
Expected number of defective watches = Proportion of defective watches x Total number of watches
Expected number of defective watches = 0.0075 x 10,500
Expected number of defective watches = 78.75
Rounding to the nearest whole number, we can estimate that we would expect approximately 79 watches to be defective out of a total of 10,500 watches based on the sample data.


that is still not correct

I apologize for the errors in my previous responses. Here is the correct solution:
Proportion of defective watches in the sample = 3/400 = 0.0075
We can use this proportion to estimate the number of defective watches in the entire population:
Expected number of defective watches = Proportion of defective watches x Total number of watches
Expected number of defective watches = 0.0075 x 10,500
Expected number of defective watches = 78.75
Rounding the expected number of defective watches to the nearest integer, we get:
Expected number of defective watches = 79
Therefore, based on the sample data, we would expect approximately 79 out of 10,500 watches to be defective.