25
Generally speaking an x% confidence interval has a margin of error of (100-x)%.
No. When multiplying by a positive number greater than 1 the number will get bigger. 0.018 is less than 1.8 so cannot be a reasonable answer to 1.8 × 100. 1.8 × 100 = 180. 1.8 ÷ 100 = 0.018.
Well...The interval is the DIFFERENCE between a number to the next on a scale.The scale is the SERIES OF NUMBERS starting at 0 to another number on the top of a graph. For example....If the graph has 0-100 numbers on it...thats the scale. The 0-100 is the scale.I hope you understand.
most reasonably it would land on 4, 1 of 6 or 16 2/3%. since it cannot land on 4 less than once the answer is 17 times of 100 throws.
157.93 plus 104.52 = 262.45Rounding to the nearest hundred this becomes 300. Rounding to the nearest ten this becomes 260.In this instance rounding to the nearest ten is more reasonable.
choose 5, 10, 25, or 100 as the most reasonable interval for 201, 450, 550, 600, 799
Interval Data: Temperature, Dates (data that has has an arbitrary zero) Ratio Data: Height, Weight, Age, Length (data that has an absolute zero) Nominal Data: Male, Female, Race, Political Party (categorical data that cannot be ranked) Ordinal Data: Degree of Satisfaction at Restaurant (data that can be ranked)
No 100 is not a reasonable estimate
100
It depends on how tightly clustered the observations are. The answer would be different if the observations were 100, 102, 104, 107, 110, ... as opposed to 100, 150, 150, 150, 150, ... , 150, 220!
Generally speaking an x% confidence interval has a margin of error of (100-x)%.
about 100 years
Yes. Simply make sure that the interval is greater than or equal to the range of the random variable.
It is misleading to say that 50% are above and 50% are below 100. The correct way to say it would be to say that 50% are at or below 100% and 50% are at or above 100. "Average" doesn't mean that number occurs most in the set of data. It means that is the middle of the set of data. Mode is the word that describes the number that occurs most in a set of data.
No.
200
1912-2011