WGU C207 Data Driven Decision Making (Verified answers) correctly answered 2023

WGU C207 Data Driven Decision Making (Verified answers) correctly answered 2023Z-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 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. 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. 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. 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. Box - Plot Used 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 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 Strong Linear Bunch around a straight line Weak Linear Scattered Negative Linear When one values decreases as the other increases Positive When both values increase together. Correlation Coefficient The 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