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Chapter 13

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Ryerson University
Quantitative Methods
QMS 202
Jason Chin- Tiong Chan

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? Winter2011 Page1 QMS202-Business Statistics II Chapter13 Scatter Diagram 1. A chart that portrays the relationship between two variables. Scatter Diagram A Winter2011 Page2 QMS202-Business Statistics II Chapter13 Scatter Diagram B Scatter Diagram C Winter2011 Page#3 QMS202-Business Statistics II Chapter13 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 ($) No. of days 8 7 3 2 5 11 4 10 12 Expenses 285 255 140 100 210 380 190 350 400 ($) Winter2011 Page4
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