WGU C207 Data Driven Decision Making

WGU C207 Data Driven Decision Making Z-Score Ans- 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 Ans- How far a set of numbers are spread. Used for Data set. Hint Words = Risk, spread. Multiplication Rule Ans- 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 Ans- 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 Ans- How many combinations can be made. Bayes Theorem Ans- 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 Ans- Number halfway into the data set. Hint Word: Typical Mode Ans- Number that occurs most often in a data set. Mean Ans- Average. Add all numbers and divide. Standard Deviation Ans- How spread out the numbers are. Square root of the variance. Pareto Chart Ans- 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 Ans- Shows the causes of a specific event. Check Sheet Ans- Collect data in real time. Control Chart Ans- Determines whether a process should undergo a formal exam for quality. Histogram Ans- 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 Ans- A graphic that uses dots to show relationships or correlations between variables Flow/Run Chart Ans- Shows the workflow process Bar Chart Ans- Graph of schedule-related info. Example: Measures how many people are from each state. Box - Plot Ans- 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 Ans- Dependent upon the Independent variable Independent Variable Ans- Variable the drives the dependent variable Range Ans- Difference between the lowest and highest number in a data set. Example: 4,6,9,3,7 Range = 9-3 =6 T-Statistic Ans- Statistic (derived from a sample) used in hypothesis testing. Determines if 2 sample means are significantly different from each other. Central Limit Theorem Ans- 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 Ans- 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 Ans- (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 Ans- 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 Ans- Bunch around a straight line Weak Linear Ans- Scattered Negative Linear Ans- When one values decreases as the other increases Positive Ans- When both values increase together. Correlation Coefficient Ans- 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 Correlation Ans- A and B may happen at the same time, but may not be related. R - Squared Ans- The term "R-squared" or "R2" provides a measure of "goodness of fit." Chi - Squared Ans- Assess 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 Programming Ans- Used to achieve best outcomes such as maximum profit or lowest cost. Give key points. Cross over Analysis Ans- Usually doesn't have revenue. Finds the intersection of two lines and shows which option is cheapest. Interval Data Ans- (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 Data Ans- Called "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 Data Ans- Data from a test that accurately measures what it is intended to measure. Reliable Data Ans- Data that is consistent and repeatable. Ration Data Ans- Data 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 Data Ans- Data that is set into some kind of order on a scale. Example: Athletes on the podium during the Olympic games. Continuous Data Ans- Data that can lay along any point. Example: Heigh