The Simple Linear Regression Model

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This report will discuss the simple linear regression model; throughout two variables, the predictor variable (independent) and one response variable (dependent) will be used to explain the models. In so doing, it explains the underlying assumptions when fitting both variables into models and statistical tools.
In addition to findings from statistical analyses, this report communicates in clear terms the significance of data on the retention rate (%) and the graduation rate (%) for the sample of 29 online colleges in the United States. With this said, Section 3 “Results” presents graphical illustrations and a scatter diagram on this relationship between the variables while Section 4 discusses the implications .
As a background for this report, the Online Education Database records that in recent times, online universities have experienced rapid growth. However, this presents some challenges to the higher education sector. In order to examine the relationship between retention rate which is denoted by RR% and graduation rate; GR% for 29 online colleges.
As a starting point, in order to determine the relationship between retention rate (RR %) and the graduation rate (GR %), variables were run through the Data Analysis add-in tool on Microsoft Excel 2013. In all, the twenty- nine (29) observations showed descriptive statistics and simple linear regression results. Following this, a scatter diagram was plotted to illustrate the linear relationship
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