Standard Deviation from Expected Values
Authored by Anthony Clark
Mathematics
11th Grade
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15 questions
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1.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What is the last step in solving for standard deviation, according to Dr. Story?
"Unsquaring" your SS
"Unsquaring" the variance
"Unsquaring" the deviation scores
"Unsquaring" your degrees of freedom
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
For a distribution of scores with μ = 50 and X = 53, what is your deviation score?
0
-3
1
3
Answer explanation
A deviation is a score's distance from the mean and uses the formula: X - μ. Using this formula, we should calculate 53 - 50 = 3.
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which of the following represents the amount of spread, dispersion, or variability of the items in a distribution?
mean or expected value
median and mode
outcomes and probability distribution
variance and standard deviation
4.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
How would you interpret a very small variance or standard deviation but not equal to zero?
The values of the random variables are farther from the mean.
The values of the random variables are nearer to the mean.
The values of the random variables are equal to the mean.
The values of the random variables have no relationship with the mean.
5.
OPEN ENDED QUESTION
1 min • 1 pt
What formula is described by σ2 = ∑[x2 * P(x)] − u2?
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6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which of the following is NOT a property of the variance?
The variance is not equal to the standard deviation.
A small variance means that the distribution of the random variable is narrowly concentrated around the mean.
A large variance means that the distribution is spread out, with some chance of observing values at some distance from the mean.
The value of the variance is less than zero.
7.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Which of the following rules state that almost all data fall within the 1, 2, and 3 Standard Deviation of the Mean when the population is normally distributed?
Empirical rule
Lottery rule
Pascal’s triangle rule
Sampling rule
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