WGU C207 Data Driven Decision Making

WGU C207 Data Driven Decision Making 12 studiers recently 4.6 (5 reviews) Students also studied Terms in this set (76) Western Governors UniversityC 207 Save WGU Data Driven Decision Making -...146 terms clouserjenPreview

C207 Pre-Assessment: Data-Driven ...

73 terms nmjohnson1987 Preview C207 Data Driven Decision Making Teacher 240 terms Calise_Brogdon3 Preview WGU - Teacher ziao Practice questions for this set Learn1 / 7Study using Learn Usually doesn't have revenue. Finds the intersection of two lines and shows which option is cheapest.Z-ScoreData 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.VarianceHow far a set of numbers are spread. Used for Data set. Hint Words = Risk, spread.Choose an answer 1Cross over Analysis2Cluster Analysis 3Decision Analysis4Check Sheet Don't know?

Multiplication RuleA 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

Addition RuleA 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.

Combination RuleHow many combinations can be made.Bayes TheoremProbability 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.

MedianNumber halfway into the data set. Hint Word: Typical

ModeNumber that occurs most often in a data set.MeanAverage. Add all numbers and divide.Standard DeviationHow spread out the numbers are. Square root of the variance.Pareto ChartContains both line and bar graphs. Ordered by frequency of occurrence that shows how many results were generated by each identified cause.Cause and Effect DiagramShows the causes of a specific event.Check SheetCollect data in real time.Control ChartDetermines whether a process should undergo a formal exam for quality.HistogramGraph 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.Scatter DiagramA graphic that uses dots to show relationships or correlations between variables Flow/Run ChartShows the workflow process Bar ChartGraph of schedule-related info. Example: Measures how many people are from each state.Box - PlotUsed while studying the composition of a data set to examine the distribution (non - parametric data) uses median and percentiles rather than averages. (Look for Spread and Median.) Dependent VariableDependent upon the Independent variable

Independent VariableVariable the drives the dependent variable

RangeDifference between the lowest and highest number in a data set. Example:

4,6,9,3,7 Range = 9-3 =6 T-StatisticStatistic (derived from a sample) used in hypothesis testing. Determines if 2 sample means are significantly different from each other.Central Limit TheoremDistribution 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-StatisticValue 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 RegressionDescribes 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 Strong LinearBunch around a straight line Weak LinearScattered Negative LinearWhen one values decreases as the other increases PositiveWhen both values increase together.Correlation CoefficientThe strength of a linear relationship.A number between -1 and 1 Close to 0 means a weak linear relationship Closer to -1 or 1 means strong linear relationship Equal to exactly -1 or 1 considered perfectly linear Negative linear relationships have correlations less than 0 Strong linear relationships have correlations great than 0 CorrelationA and B may happen at the same time, but may not be related.R - SquaredThe term "R-squared" or "R2" provides a measure of "goodness of fit."

Chi - SquaredAssess the goodness of fit between observed values and those expected theoretically. A chi-squared test is commonly used in statistics to draw inferences about a population, by testing sample data. A chi-squared test is employed for categorical data.Linear ProgrammingUsed to achieve best outcomes such as maximum profit or lowest cost. Give key points.Cross over AnalysisUsually doesn't have revenue. Finds the intersection of two lines and shows which option is cheapest.Interval Data(Integer) Data this is ordered within a range with each data point being an equal

interval apart. Example: Level of happiness, degrees in Fahrenheit.

Nominal DataCalled "Categorical Data" or "Qualitative Data", data type is used to label subjects by order of name. Breaks results into categories, like days of the week, or states of the United States of America.Valid DataData from a test that accurately measures what it is intended to measure.Reliable DataData that is consistent and repeatable.Ration DataData that is ordered within a range with each data point being an equal interval apart, also has a natural zero point which indicates none of the given quality.

Example: Height, Age.

Ordinal DataData that is set into some kind of order on a scale. Example: Athletes on the podium during the Olympic games.

Continuous DataData that can lay along any point. Example: Height, Run Times

Discrete DataData that can only take on whole values and has clear boundaries. Example: Number of students in a class room.Inferential StatisticsUsed to make predictions about a population from a sample.IQR (Inter-quartile Range)The difference in value between the bottom and the top 25% of the sample.Cumulative DistributionThe probability that a random variable will be found at a value less than or equal to a given number.Confidence IntervalAn internal estimate used to indicate reliability.ComplementThe occurrence of an event not happening, the opposite.Descriptive StatisticsStatistics that are used to describe a population from observations of that whole population.Standard Error of the MeanAn estimate of the distance between the sample mean and the population mean.