Simple Linear Regression in SPSS 1. STAT 314 Ten Corvettes between 1 and 6 years old were randomly selected from last year’s sales records in Virginia Beach‚ Virginia. The following data were obtained‚ where x denotes age‚ in years‚ and y denotes sales price‚ in hundreds of dollars. x y a. b. c. d. e. f. g. h. i. j. k. l. m. 6 125 6 115 6 130 4 160 2 219 5 150 4 190 5 163 1 260 2 260 Graph the data in a scatterplot to determine if there is a possible linear relationship. Compute and interpret
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Introduction to Linear Regression and Correlation Analysis Goals After this‚ you should be able to: • • • • • Calculate and interpret the simple correlation between two variables Determine whether the correlation is significant Calculate and interpret the simple linear regression equation for a set of data Understand the assumptions behind regression analysis Determine whether a regression model is significant Goals (continued) After this‚ you should be able to: • Calculate and
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Limitations: Regression analysis is a commonly used tool for companies to make predictions based on certain variables. Even though it is very common there are still limitations that arise when producing the regression‚ which can skew the results. The Number of Variables: The first limitation that we noticed in our regression model is the number of variables that we used. The more companies that you have to compare the greater the chance your model will be significant. We have found that
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1 CORRELATION & REGRESSION 1.0 Introduction Correlation and regression are concerned with measuring the linear relationship between two variables. 1.1 Scattergram It is not a graph at all‚ it looks at first glance like a series of dots placed haphazardly on a sheet of graph paper. The purpose of scattergram is to illustrate diagrammatically any relationship between two variables. (a) If the variables are related‚ what kind of relationship it is‚ linear or nonlinear
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Types of regression and linear regression equation 1. The term regression was first used as a statistical concept in 1877 by Sir Francis Galton. 2. Regression determines ‘cause and effect’ relationship between variables‚ so it can aid to the decision-making process. 3. It can only indicate how or to what extent variables are associated with each other. 4. There are two types of variables used in regression analysis i.e. The known variable is called as Independent Variable and the variable which
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Chapter 8 Cost Estimation and Budgeting 8.1 True/False 1) Direct costs are those clearly assigned to the aspect of the project that generated the cost. Answer TRUE 2) Material is an example of a cost that is recurring‚ variable and direct. Answer TRUE 3) An expedited cost is one that does not vary with respect to their usage. Answer FALSE 4) An order of magnitude estimate is usually more accurate than a ballpark estimate. Answer FALSE 5) Comparative estimates are more accurate than definitive
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Problems Chap. 4: 6‚ 10‚ 15‚ 17‚ 23‚ 28‚ 33 and 42 Session 3 Probability Distributions Chap. 5 and 6 Session 4 Problems Chap. 5: 7‚ 8‚ 18‚ 30‚ 39‚ 42 and 50 Problems Chap. 6: 1‚ 4‚ 13‚ 15‚ 18‚ 28 and 35 Session 4 Sampling and Interval Estimation Chap. 7 and 8 Session 5 Problems Chap. 7: 11‚ 13‚ 19‚ 23‚ 32‚ and 35 Problems Chap. 8: 2‚ 5‚ 15‚ 25‚ 31 and 39 Session 5 Hypothesis Testing Chap. 9 Session 6 Problems Chap. 9: 2‚ 5‚ 10‚ 11‚ 15‚ 24‚ 27‚ 36‚ and 38 Session 6 Mid-Term Exam
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Topic 8: Multiple Regression Answer a. Scatterplot 120 Game Attendance 100 80 60 40 20 0 0 5‚000 10‚000 15‚000 20‚000 25‚000 Team Win/Loss % There appears to be a positive linear relationship between team win/loss percentage and game attendance. There appears to be a positive linear relationship between opponent win/loss percentage and game attendance. There appears to be a positive linear relationship between games played and game attendance. There does not appear to be any relationship
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Tupperware Corporation‚ moderate) 2. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product. True (What is forecasting? moderate) 3. Sales forecasts are an input to financial planning‚ while demand forecasts impact human resource decisions. True (Types of forecasts‚ moderate) 4. Forecasts of individual products tend to be more accurate than forecasts of product families. False (Seven steps in the forecasting system‚ moderate) 5. Most
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Regression Analysis (Tom’s Used Mustangs) Irving Campus GM 533: Applied Managerial Statistics 04/19/2012 Memo To: From: Date: April 19st‚ 2012 Re: Statistic Analysis on price settings Various hypothesis tests were compared as well as several multiple regressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35 used Mustangs and 10 different characteristics. The test hypothesis that
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