Simple Linear Regression Analysis

Simple Linear Regression Analysis 1
Simple Linear Regression Analysis
Institution Name
Student Name

Simple Linear Regression Analysis 2
Simple Linear Regression Analysis
Purpose
In this report the focus will be identifying the association between the retention rate
(RR) and the graduation rate (GR). The two ratios can be used by prospecting students to
gauge the quality of education offered by an institution prior to enrolling in one. (Morris
2018). By comparing the ratios, a student is able to have a criterion for favouring one college
against the other.
Background
Internet coverage is quickly spreading across the globe, moreover individuals are in
need of flexible schedules due to hectic lifestyles. This have combined to make online studies
more and more attractive to many students. Most people especially those undertaking higher
education themselves with tight routines and often have minimal time to travel to colleges so
as to attend classes. Online programmes are defined as courses that students undertake
through computers rather than physically attending classes. The programmes can be taken
while at home or even in offices (Craig 2015). To meet the demand for online courses a
number of institutions have opened up their branches to offer these programmes. In addition
to this, others have cropped up just to avail online educational services. The widely spreading
online learning has left students with a hard choice when it comes to the best institution to
enrol to for the purpose of higher learning.
To assist students with a way of selecting the best institution to attend, economics can
apply the two rates to rank institutions based on quality provision (Sabbah 2011). First the
RR is the percentage of first year first time students who enrol in the school for their second-
year programme. The graduation rate on the other hand is the percentage of the students
admitted in the school in first year who goes ahead and completes their studies within 150%
of the recommended time needed to finalise a course (Anstine 2013).
Method
In this report the analysis entailed a sample data obtained from the Online Educational
database. Out of the secondary data that the organisation collects from accredited universities
to offer online courses, a sample of 29 colleges were selected at random and their RR and GR
noted for the analysis. The use of secondary data is vital for the study as it is more reliable
(Long 2009). As a way of determining the correlation between the two variables a scatter plot

Simple Linear Regression Analysis 3
was drawn in addition to estimating a linear regression equation. Furthermore, the reliability
of the, model was gauged by modelling a simple linear regression. The analysis was done
using the Microsoft Excel.
Results
a. When the descriptive statistics of the two variables are derived the tables below is
obtained.
Descriptive Statistics
RR(%) GR(%)
Mean 57.4138 Mean 41.7586
Standard Error 4.3156 Standard Error 1.8320
Median 60 Median 39
Mode 51 Mode 36
Standard Deviation 23.2402 Standard Deviation 9.8657
Sample Variance 540.1084 Sample Variance 97.3325
Kurtosis 0.4618 Kurtosis -0.8824
Skewness -0.3099 Skewness 0.1764
Range 96 Range 36
Minimum 4 Minimum 25
Maximum 100 Maximum 61
Sum 1665 Sum 1211
Count 29 Count 29
Largest(1) 100 Largest(1) 61
Smallest(1) 4 Smallest(1) 25
b. A scatter plot assists have a visual outlay of the relationship between the two variables
as represented in the chart.