A company claims that each batch of its deluxe mixed nuts contains 52% cashews, 27% almonds, 13% macadamia nuts, and 8% Brazil nuts. To test this claim, a quality-control inspector takes a random sample of 150 nuts from the latest batch. The table displays the sample data. Type of nut Cashew Almond Macadamia Brazil Count 83 29 20 18 The inspector has also calculated the expected counts for each type of nut: Cashew = 78, Almond = 40.5, Macadamia = 19.5, Brazil = 12. The Random condition is met. Can the inspector use a chi-square distribution to calculate the P-value? ΟΟ Because at least one expected count is greater than 30, the inspector can use a chi-square distribution. Because all expected counts are not greater than 30, the inspector cannot use a chi-square distribution. Because all observed counts are greater than 5, the inspector can use a chi-square distribution. Because the distribution of counts is approximately normal, the inspector can use a chi-square distribution. Because all expected counts are greater than 5, the inspector can use a chi-square distribution.

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A company claims that each batch of its deluxe mixed nuts contains 52% cashews, 27% almonds, 13% macadamia nuts, and 8%
Brazil nuts. To test this claim, a quality-control inspector takes a random sample of 150 nuts from the latest batch. The table
displays the sample data.
Type of nut Cashew Almond Macadamia Brazil
Count
83
29
20
18
19.5,
The inspector has also calculated the expected counts for each type of nut: Cashew = 78, Almond = 40.5, Macadamia =
Brazil = 12.
The Random condition is met. Can the inspector use a chi-square distribution to calculate the P-value?
Because at least one expected count is greater than 30, the inspector can use a chi-square distribution.
Because all expected counts are not greater than 30, the inspector cannot use a chi-square distribution.
Because all observed counts are greater than 5, the inspector can use a chi-square distribution.
Because the distribution of counts is approximately normal, the inspector can use a chi-square distribution.
Because all expected counts are greater than 5, the inspector can use a chi-square distribution.
Transcribed Image Text:A company claims that each batch of its deluxe mixed nuts contains 52% cashews, 27% almonds, 13% macadamia nuts, and 8% Brazil nuts. To test this claim, a quality-control inspector takes a random sample of 150 nuts from the latest batch. The table displays the sample data. Type of nut Cashew Almond Macadamia Brazil Count 83 29 20 18 19.5, The inspector has also calculated the expected counts for each type of nut: Cashew = 78, Almond = 40.5, Macadamia = Brazil = 12. The Random condition is met. Can the inspector use a chi-square distribution to calculate the P-value? Because at least one expected count is greater than 30, the inspector can use a chi-square distribution. Because all expected counts are not greater than 30, the inspector cannot use a chi-square distribution. Because all observed counts are greater than 5, the inspector can use a chi-square distribution. Because the distribution of counts is approximately normal, the inspector can use a chi-square distribution. Because all expected counts are greater than 5, the inspector can use a chi-square distribution.
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