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Unformatted text preview: Lecture 22: Inferential Statistics / Simple Regression Chapter 12 (12.6, 12.7) PS7 Please download: • Supermarket.xls • Rent.xls • Delivery.xls Simple Linear Regression Review: Simple Linear Regression (Chapter 12.1, 12.2) 1. How to use regression analysis to predict the value of a dependent variable based on an independent variable 2. The meaning of the regression coefficients b0 and b1 3. Use regression to predict individual values Review: Simple Linear Regression (Chapter 12.3, 12.5) 1. How do you evaluate the strength of the relationship ? 2. What assumptions need to be checked when you use regression? 3. How do you check the assumptions? What to do when they are violated? New Material (Chapter 12.6, 12.7) 1. Use regression to make inferences about the slope and correlation coefficient 2. Use regression to estimate mean values Review : Regression Regression analysis enables you to develop a model: – To predict the value of a numerical (dependent) variable based on the value of at least one numerical (independent) variable – Explain the impact of changes in an independent variable on the dependent variable Simple Linear Regression Model:  Only one independent variable, X Relationship between X and Y is described by a linear function Changes in Y are assumed to be caused by changes in X REVIEW: Simple Regression Model enables you to: • To predict the value of a numerical (dependent) variable based on the value of one numerical (independent) variable • Explain the impact of changes in an independent variable on the dependent variable – Box office revenue (in $ millions) ‚ DVD sales (in thousands) – Size of houses & house prices Relationship between X and Y is described by a linear function Example 1. Problem 12.7 A critically important aspect of customer service in a supermarket is the waiting time at the checkout (defined as the time the customer enters the line until he or she is served). Data were collected during time periods when a constant number of checkout counters were open. The total number of customers in the store and the waiting time (in minutes) were recorded (file ‘Supermarket.xls’) a) Construct a scatter plot . – Highlight last two columns of the data, insert Scatter Plot (with Excel or PHStat) – Once you have the scatter plot, place the cursor over one of the data points and right click. Select ‘Add Trendline’ and select ‘Display Equation’. b) Assuming a linear relationship, use the leastsquares method to find the regression coefficients b0 and b1 – The equation you got from a) is the regression equation using leastsquares method, so you can find regression coefficients from that equation – Or you can get the regression coefficients with Option 2 or Option 3 (see Lecture 20) Problem 12.7, file ‘Supermarket.xls’ PHStat: ‘Regression’, ‘Simple Linear Regression’, click ‘Regression Statistics Table’, ‘ANOVA and Coefficients Table’, ‘Scatter diagram’ a) Construct a scatter plot...
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 Spring '08
 Abousayf,F
 Regression Analysis, linear relationship, regression coefficients, population slope

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