Answer:
The correct answer is:
the amount of difference expected just by chance (b)
Step-by-step explanation:
Standard error in hypothesis testing is a measure of how accurately a sample distribution represents a distribution by using standard deviation. For example in a population, the sample mean deviates from the actual mean, the mean deviation is the standard error of the mean, showing the amount of difference between the sample mean and the actual mean, occurring just by chance. Mathematically standard error is represented as:
standard error = (mean deviation) ÷ √(sample size).
standard error is inversely proportional to sample size. The larger the sample size, the smaller the standard error, and vice versa.
In one third you would need 12 one thirds to make a whole sixth
Is it either C or D not 100% but it is one of those hope this helped
The answer is (14) just add them all up
53: 800 and 900
54: 700 and 800
55: 500 and 600
56: 2,771,100 and 2,771,200
57: 90,120,000 and 90,120,100
58: 631,900 and 632,000
59: 93,300 and 93,400
60: 200 and 300
61: 900 and 1000
62: 39,576,700 and 39,576,800
63: 24,900 and 25,000
64: 471,100 and 471,200
