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Unformatted text preview: ANOVA b 2314.092 1 2314.092 587.655 .000 a 413.473 105 3.938 2727.565 106 Regression Residual Total Model 1 Sum of Squares df Mean Square F Sig. Predictors: (Constant), CARAT a. Dependent Variable: PRICE b. Model Summary .921 a .848 .847 1.98440 Model 1 R R Square Adjusted R Square Std. Error of the Estimate Predictors: (Constant), CARAT a. Model Summary .966 a .932 .930 1.34506 Model 1 R R Square Adjusted R Square Std. Error of the Estimate Predictors: (Constant), CUT, CLARITY, CARAT, COLOR a. ANOVA b 2543.028 4 635.757 351.406 .000 a 184.536 102 1.809 2727.565 106 Regression Residual Total Model 1 Sum of Squares df Mean Square F Sig. Predictors: (Constant), CUT, CLARITY, CARAT, COLOR a. Dependent Variable: PRICE b. STAS2126 Assignment#5 (Summer 2008) Download assignment BEFORE answering the questions: DON’T answer the questions within Blackboard (this can lead to problems). Submit completed assignment to the Digital Dropbox. SHOW YOUR WORK FOR ALL CALCULATION QUESTIONS. DUE ON MONDAY MAY 26 AT 11:00 PM The Diamond File: This file contains information about real diamonds that were being sold on an Internet site that I found. I downloaded the information and created an SPSS file with actual data provided for each diamond. People who know diamonds (I don’t), refer to the five Cs: Carat, Color, Clarity, Cut and, of course, Cost. These factors are represented in the SPSS data file. One purpose of this lab will be to understand how important carat size (IV) is in determining the price (DV) of diamonds. How much of the variance in price is determined by Carat size and how much by other factors? Carat = Number of carats Color = How close stone is to colorlessness Clarity = the number of imperfections Cut (in this file, cut is a composite score based on 5 characteristics: Depth, Table, Symmetry , Shape, Polish) Step 1: Correlation 1a The size of correlation between Carat and Price is .921. How much of the variation in Price of diamonds does Carat size explain (in %)? % variance = .921 x .921 = 0.848 = 84.8% 1b Use a single statement to explain or describe what the positive correlation between Carat and Price means. As the number of carats increases, so does the price of the diamond Step 2: Linear Regression Linear regression is generally used for prediction. In this case, we are going to predict diamond Price (the DV) by using Carat size as the predictor (or IV). In the SPSS output, Price is the Dependent variable and Carat as the Independent variable. Notice the ANOVA table…Regression sum of squares= Between groups…Residual = Within groups sum of squares 2a Look at portion of output called “Model Summary”…what is the value of R indicated there? r = .921 2b Check “Model Summary” again to find R square…what is this value as a % and how does it...
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- Fall '08
- Regression Analysis, body dissatisfaction, Model Summary, carat size