WGU C955 EXAM SCRIPT 2026 COMPLETE
QUESTIONS AND VERIFIED ANSWERS
⩥ Histogram - when to use. Answer: Based on the shape of the
distribution, uses mean +
standard deviation OR
median + IQR to describe
center and spread - Larger data sets; shows
shapes of distribution and
potential outliers; ignores the
individual data valuesl
⩥ Histogram Skewed right. Answer: Not a symmetric distribution, the
tail is on the right
⩥ Standard Deviation Rule. Answer: 68% of the data are within 1
standard deviation,
95% are within 2,
99.7% are within 3 standard deviations from the mean.
⩥ Scatter plot. Answer: A graphical representation of Q -> Q
If relationship is linear (confirmed
, using the scatterplot), use the
correlation coefficient to describe
strength of relationship and the
least-squares regression line to make
predictions
⩥ Two way table. Answer: A graphical representation of C -> C
Relative frequencies OR conditional
percentages for each row/column of
the explanatory variable
⩥ Side-by side box. Answer: A graphical representation of C -> Q
5-number summaries of the response
variables
⩥ Interpolation. Answer: Making predictions *within* the range of your
data. This is usually accurate.
⩥ Extrapolation. Answer: Making predictions *outside* of the range of
your data. This is generally a bad idea.
predictions for data larger than the maximum x-value or smaller than the
minimum x-value of the known data points
QUESTIONS AND VERIFIED ANSWERS
⩥ Histogram - when to use. Answer: Based on the shape of the
distribution, uses mean +
standard deviation OR
median + IQR to describe
center and spread - Larger data sets; shows
shapes of distribution and
potential outliers; ignores the
individual data valuesl
⩥ Histogram Skewed right. Answer: Not a symmetric distribution, the
tail is on the right
⩥ Standard Deviation Rule. Answer: 68% of the data are within 1
standard deviation,
95% are within 2,
99.7% are within 3 standard deviations from the mean.
⩥ Scatter plot. Answer: A graphical representation of Q -> Q
If relationship is linear (confirmed
, using the scatterplot), use the
correlation coefficient to describe
strength of relationship and the
least-squares regression line to make
predictions
⩥ Two way table. Answer: A graphical representation of C -> C
Relative frequencies OR conditional
percentages for each row/column of
the explanatory variable
⩥ Side-by side box. Answer: A graphical representation of C -> Q
5-number summaries of the response
variables
⩥ Interpolation. Answer: Making predictions *within* the range of your
data. This is usually accurate.
⩥ Extrapolation. Answer: Making predictions *outside* of the range of
your data. This is generally a bad idea.
predictions for data larger than the maximum x-value or smaller than the
minimum x-value of the known data points
