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2.2
Central Tendency
Question | Answer |
---|---|
Spread of the data | Standard Deviation A normally distributed sample spreads from -3 to +3 standard deviations from the mean |
We should not use this measure of central tendency alone for decisions because it includes outliers | Mean |
The best measure of central tendency when making decisions | Median |
We use this measure of central tendency if we want to know what happens the most | Mode (most can also be defined as typical or common) |
If the mean is 50 and the standard deviation is 5, what is the probability of being between 45 and 55? | 68.2% (of the sample will be within 1 standard deviation of the mean) 50 - 5 = 45 and 50 + 5 + =55 |
What are the three probabilities of the bell curve? | 68.2% 95.4% 99.7% |
68.2% of a sample will be within _______ standard deviation of the mean. | 1 |
95.4% of a sample will be within ______ standard deviations of the mean. | 2 |
99.7% of a sample will be within _____ standard deviations of the mean. | 3 |
The mean is 20 and the standard deviation is 2, what is the probability of being between 14 and 26 | 99.7% (of the sample will be within 3 standard deviations of the mean) 20 + 2 + 2 + 2 = 26 and 20 - 2 - 2 - 2 = 14 |
_______ can be used to differentiate between two samples with the same mean. | Variation |
Which measurement can tell us where a single data point is on the bell curve? | z-score. (Tip: Remember z for me. Where are you in the curve of your peers) |
You want to know how your height compares to all of your family tree. How do you calculate a z score? | (Your height - the mean of the family tree height) divided by the standard deviation of the family tree height (me-mean)/standard deviaiton |
You are 63" tall and the family tree averages 67" with a standard deviation of 2". What is your z-score? | (63-67)/2 = -2 You are 2 standard deviations shorter than the family tree. |
Which measure lets you measure your height compared to your maternal family tree and your height compared to your paternal family tree? | z-scores let us measure two samples by putting them to the same scale. |