WGU Data Driven Decision Making - C207 questions with verified answers

WGU Data D riven Decision Making - C207 questions with verified answers Activities (RBM stage) -Correct Answer-second step involves the process that converts inputs to outputs (actions necessary to produces results - training, evaluating, developing) Alternative hypothesis -Correct Answer-The argument that either a sample is not equal to, greater than, or less than the hypothesized null sample Analysis of Variance (ANOVA) -Correct Answer-a technique used to determine if there is a sufficient evidence from sample data of three or more populations to conclude that the means of the population are not all equal Analytics -Correct Answer-The discovery, analysis, and communication of meaningful patterns in data. Autocorrelation -Correct Answer-A relationship between two variables that is inherently non-linear Balanced Scorecard -Correct Answer-An approach using multiple measures to evaluate performance, including financial measures, and the non-financial measures of customers, internal business processes, and learning and growth. Bar chart -Correct Answer-A graph that measures the distribution of data over discrete groups or categories. Benchmarks -Correct Answer-Standards or points of reference for an industry or sector that can be used for comparison and evaluation. Big Data -Correct Answer-very large amounts of data; an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications Blind Study -Correct Answer-A study performed where the participants are not told if they are in the treatment group or control group body mass index (BMI) -Correct Answer-A measure, based on a person's weight and height, that is used to classify people as underweight or overweight. Business process -Correct Answer-A sequence of logically related and time based work activities to provide a specific output for a customer. Central Limit Theorem -Correct Answer-A theorem that states that, the greater the sample, the closer the mean of the sample is to the entire population and the more the results will look like a normal distribution