Data Driven Decision Making- C207
Western Governors University
December 11, 2023
C207 TASK 1 DATA DRIVEN DECISION MAKING .
lOMoAR cPSD|
1
A. The data provided in this scenario points out the turnover rate of nursing staff which resulted
in implementing an employee wellness program. Based on ...
A. The data provided in this scenario points out the turnover rate of nursing staff which resulted
in implementing an employee wellness program. Based on this analysis, the question that can be
asked will be: Does implementing an employee well-being program that provides incentives
affect the attrition rate of nursing staff? Is it possible to reduce the rate of attrition of nurses at a
major healthcare system by implementing a voluntary employee well-being program that
provides incentives?
B1. - Independent Variable: In this scenario, the wellness program participation (%) is the
independent variable. It is represented on the x axis.
- Dependent Variable: In this scenario, the nursing attrition rate (5) is the dependent
variable, and is represented on the y axis. The investigators can study a line of regression using
the data from the previous 36 months since the wellness program was initiated to determine if
there is a relationship or trend between the independent and dependent variables.
- Type of Data: The attrition rate is proved as a percentage, and indicates the ratio of
nurses left compared to those who remain employed. In spite of the fact that this number can be
zero, these data points are considered continuous ratios.
- Quantity of Data: During the 36 months of the study, two data points were collected:
attrition rate and program participation rate. The total number of data points collected is 72. The
regression model examines 36 data points.
B2 and C1. Please refer to the Excel Spreadsheet
C2. Since the data is continuous, a linear regression analysis is appropriate, it will explain
how a continuous variable can affect a dependent variable. By examining the overall line of best
fit, the linear regression can be used to examine trends and predict future relationships between
program participation and nursing staff retention.
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