WGU C207 Data Driven Decision Making Updated 2024/2025 Verified 100%
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Module
WGU C207 Data Driven Decision Making
Institution
WGU C207 Data Driven Decision Making
Histogram - ️️Graph representing the distribution of numeric data. Measures how
continuous data is distributed over various ranges. Example: Displays how many people
fall in various ranges of height.
Addition Rule - ️️A method for finding the probability that either or both of two
event...
WGU C207 Data Driven Decision Making
Histogram - ✔️✔️Graph representing the distribution of numeric data. Measures how
continuous data is distributed over various ranges. Example: Displays how many people
fall in various ranges of height.
Addition Rule - ✔️✔️A method for finding the probability that either or both of two
events occur. When two events, A and B, are mutually exclusive, the probability that A
or B will occur is the sum of the probability of each event. Word Hint: Either/or.
Z-Score - ✔️✔️Data points only. Measurement of a scores relationship to the mean. A
statistical measure that indicates the number of standard deviations a data point is from
its mean.
Variance - ✔️✔️How far a set of numbers are spread. Used for Data set. Hint Words =
Risk, spread.
Multiplication Rule - ✔️✔️A method for finding the probability that both of two events
occur. When the probabilities of multiple events are multiplied together to determine the
likelihood of all of the events happening. Word Hint: And
Combination Rule - ✔️✔️How many combinations can be made.
Bayes Theorem - ✔️✔️Probability of an event , based on conditions that might be
related to the event. Conditional probability. A formula that calculates conditional
probabilities. Important for understanding how new information affects the probabilities
of outcomes. Word Hint: Given that.
Median - ✔️✔️Number halfway into the data set. Hint Word: Typical
Mode - ✔️✔️Number that occurs most often in a data set.
Mean - ✔️✔️Average. Add all numbers and divide.
Standard Deviation - ✔️✔️How spread out the numbers are. Square root of the
variance.
Pareto Chart - ✔️✔️Contains both line and bar graphs. Ordered by frequency of
occurrence that shows how many results were generated by each identified cause.
Cause and Effect Diagram - ✔️✔️Shows the causes of a specific event.
, Check Sheet - ✔️✔️Collect data in real time.
Control Chart - ✔️✔️Determines whether a process should undergo a formal exam for
quality.
Scatter Diagram - ✔️✔️A graphic that uses dots to show relationships or correlations
between variables
Flow/Run Chart - ✔️✔️Shows the workflow process
Bar Chart - ✔️✔️Graph of schedule-related info. Example: Measures how many people
are from each state.
Dependent Variable - ✔️✔️Dependent upon the Independent variable
Independent Variable - ✔️✔️Variable the drives the dependent variable
Range - ✔️✔️Difference between the lowest and highest number in a data set.
Example: 4,6,9,3,7 Range = 9-3 =6
T-Statistic - ✔️✔️Statistic (derived from a sample) used in hypothesis testing.
Determines if 2 sample means are significantly different from each other.
Central Limit Theorem - ✔️✔️Distribution of average of a large number of independent,
identical, variables will be approximately normal. OR the idea that if a large enough
number of samples is taken, the means of those samples will be normally distributed
around the population mean.
F-Statistic - ✔️✔️Value you get when you run an ANOVA test or a regression analysis
to find out if the means between two populations are significantly different.
ANOVA - ✔️✔️(Analysis of Variance) - Collection of statistical models used to analyze
the differences among group means, (Three or more groups) Compares samples over
different times. Uses same software as regression, but takes multiple sets of data and
tries to find the difference between the groups. At least three groups of data and sees if
there is any statistical value. Used to determine if there is a significant difference among
three or more means.
Linear Regression - ✔️✔️Describes data and explains the relationship between one
dependent variable and one more independent variables. Predictive analysis. Linear
relationship between two variables can be measured by its strength
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