# In a random sample of 400 watches, 3 are defective. Out of a total of 10,500 watches, how many would you expect to be defective based on this sample data?

1 year ago

## 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.

1 year ago

1 year ago

## 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.

1 year ago

1 year ago

## 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.

8 months ago

## To calculate the expected number of defective watches based on the sample data, we can use the concept of proportions.

First, we need to determine the proportion of defective watches in the sample:
Proportion of defective watches in the sample = (Number of defective watches in the sample) / (Total number of watches in the sample)
= 3 / 400
= 0.0075

Now, we can use this proportion to estimate the number of defective watches in the total population:
Number of defective watches in the total population = (Proportion of defective watches in the sample) * (Total number of watches in the total population)
= 0.0075 * 10,500
= 78.75

Rounding to the nearest whole number, we can expect approximately 79 watches to be defective based on this sample data.

7 months ago

## To determine the expected number of defective watches in the total population based on the sample data, we can use the concept of proportionality.

First, let's calculate the proportion of defective watches in the sample:
Proportion of defective watches in the sample = (Number of defective watches in the sample) / (Total number of watches in the sample)
Proportion of defective watches in the sample = 3 / 400

Next, we can use this proportion to estimate the expected number of defective watches in the total population:
Expected number of defective watches in the total population = (Proportion of defective watches in the sample) Ã— (Total number of watches in the total population)
Expected number of defective watches in the total population = (3 / 400) Ã— 10,500

Using this calculation, you can estimate the expected number of defective watches in the total population based on the given sample data.

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