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.
Answer:
We can use a trick here. Let's look at the first few exponents of i to realize this:
i^0 = 1
i^1 = i
i^2= -1
i^3 = -i
i^4 = 1
i^5 = i
i^6 = -1
i^7 = -i
we can see that the pattern (1, i, -1, -i) repeats. Since 82/2 = 41, and 41 is only divisible by 1, i^41 = i, and i^2 = -1. -1*i = -i, so i^82 = -i.
Step-by-step explanation:
Answer:
It's 0 I think I'm not sure (I'm sure it's 0 but That's what I always say to humble myself so)
Step-by-step explanation: