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Lecture

# Chapter 13

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Ryerson University

Quantitative Methods

QMS 202

Jason Chin- Tiong Chan

Winter

Description

QMS202-Business Statistics II Chapter13
Chapter13 Simple Linear Regression
Outcomes:
1. Construct a scatter diagram
2. Understand and interpret the terms dependent variable and
independent variable
3. Calculate a least squares regression line
4. Determine and interpret the coefficient of correlation, the coefficient
of determination, and the standard error of estimate
5. Conduct a test of hypothesis for a population slope, using t Test
6. Interpret an ANOVA table
Simple Regression Analysis
1. Simple Regression Analysis is the process of constructing a
mathematical model that can be used to predict one variable
(dependent variable) by another variable (independent variable)
2. Dependent variable: the variable we wish to predict and denoted
by y
3. Independent variable: the variable used to make the prediction
and denoted by x
4. Regression analysis with two or more independent variables is
called multiple regression analysis.
Example1
For each question, identify the dependent and independent variables
a. Does the number of litres of gasoline sold depend on the volume of
traffic?
b. Does the number of meals sold in a cafeteria depend on the
number of employees?
c. Does sales revenue depend on advertising expenditure?
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Scatter Diagram
1. A chart that portrays the relationship between two variables.
Scatter Diagram A
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Scatter Diagram B
Scatter Diagram C
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Example2
The duration of the last 18 business trips made by an employee and
the corresponding expenses claimed are shown in the following table.
No. of days 3 5 2 1 3 6 8 7 9
Expenses 140 200 110 100 135 230 290 260 310
($)
No. of days 8 7 3 2 5 11 4 10 12
Expenses 285 255 140 100 210 380 190 350 400
($)
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