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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?

5 answers

  1. 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.

  2. that isnt correct

  3. 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.

  5. that is still not correct

  6. 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.

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