Answer:
Step-by-step explanation: 56776
Answer:
(E) The bias will decrease and the variance will decrease.
Step-by-step explanation:
Given that researchers working the mean weight of a random sample of 800 carry-on bags to e the airline.
We have to find out the effect of increasing the sample size on variance and bias.
We know as per central limit theorem, sample mean follows a normal distribution with mean = sample mean
and std deviation of sample mean = std error = 
Thus std error the square root of variance is inversely proportional to the square root of sample size.
Also whenever we increase sample size the chances of bias would decrease as the sample size becomes larger
So correct answer is both bias and variation will decrease.
(E) The bias will decrease and the variance will decrease.
A score of 85 would be 1 standard deviation from the mean, 74. Using the 68-95-99.7 rule, we know that 68% of normally distributed data falls within 1 standard deviation of the mean. This means that 100%-68% = 32% of the data is either higher or lower. 32/2 = 16% of the data will be higher than 1 standard deviation from the mean and 16% of the data will be lower than 1 standard deviation from the mean. This means that 16% of the graduating seniors should have a score above 85%.
Y equals 5 over 7x minus 5
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