COMPLETE STUDY GUIDE WITH ANSWERS
⩥ The Empirical Rule. Answer: According to The Empirical Rule,
approximately 68% of the data points in a dataset will be within 1
standard deviation of the mean. 95% of all values are within 2 standard
deviations of the mean.
⩥ Normal distribution. Answer: In a normal distribution data is
symmetrical, so the mean, median, and mode are all equal.
⩥ measure of spread. Answer: Measures of spread describe how similar
or varied the set of observed values are for a particular variable (data
item). Measures of spread include the range, quartiles and the
interquartile range, variance and standard deviation.
⩥ Standard Deviation Rule 2 and 3 deviations. Answer: According the
the Standard Deviation Rule, approximately 2.35 percent of all values
will fall between 2 and 3 standard deviations above the mean.
⩥ How are the mode and mean of a sample related if the distribution is
positively skewed?. Answer: The mode is less than the mean.
, ⩥ A set of data is normally distributed with a mean of 85 and standard
deviation 20. The data point values that fall within one standard
deviation range from ___________ to ___________?. Answer: We know
that the standard deviation is 20. To obtain the values that are one
standard deviation above and below the mean, we do the following: To
obtain the first value, we will subtract 20 from the mean: 85 −20 =65 To
obtain the second value, we will add 20 to the mean: 85 +20 =105
Therefore, the data values that will fall within 1 standard deviation of the
mean will range from 65 to 105.
⩥ best used to display categorical data. Answer:
⩥ How are the mean, median, and mode of a sample related if the
distribution is normally distributed?. Answer: The values are all equal
⩥ IQR (interquartile range). Answer: Q3-Q1
⩥ standard deviation. Answer: Using the Standard Deviation Rule, we
know that when data is normally distributed, 50% of the values fall
above the mean, and 50% of the values fall below the mean.
⩥ population sample from a box plot.. Answer: It is not possible to
estimate the size of the population sample from a box plot.