{"size":{"Width":500,"Height":500},"appearance":{"background":null,"padding":14,"font":{"family":"Courier New","size":10.0,"bold":false,"italic":false,"underline":false,"strikeout":false,"color":"rgb(0,72,168)"},"border":{"on":true,"size":0.0,"style":"solid","color":"#666"},"text":{"wrap":false,"hAlign":"left","vAlign":"top"}},"outputType":"WIDGET","widgetState":null,"wikiPageTitle":"Regression - Linear Regression","outputs":{"warning":"74% of the data is missing and has been excluded from the analysis. Consider either filters to ensure that the data that is missing is in-line with your expectations, or, set 'Missing Data' to another option.\r\nUnusual observations detected. The largest studentized residual is 6.36, which is significant, with a Bonferroni-corrected p-value of 0.0000004.\n\nThe largest hat value is 0.205, which is higher than the threshhold of 0.0221 = 2 * (k + 1) / n.\n\r\nThe Variance Inflation Factor of the coefficients are: S1 Age: 19 to 24: 1.8; S1 Age: 25 to 29: 1.1; S1 Age: 30 to 34: 1.9; S1 Age: 35 to 39: 6; S1 Age: 40 to 44: 1; S1 Age: 45 to 49: 5; S2 Gender: Female: 1.1; C2 Work Status: Full time employment: 1.1; C2 Work Status: Part time employment: 1.1; C2 Work Status: Unemployed: 1.8; C2 Work Status: Student/not working: 1.1; C2 Work Status: Retired: 1.9. A value of 4 or more indicates the confidence interval for the coefficient is\n twice as wide as they would be for uncorrelated predictors. A value of 10 or more\n indicates high multicollinearity.\r\nA Breusch Pagan Test for non-constant variance has failed (p = 0.000000004). A plot of the residuals versus the fitted values of the\n outcome variable may be useful (Regression > Diagnostic > Plot > Residuals vs Fitted).\n A transformation of the outcome or predictor variables may solve this problem. Or, consider using Robust Standard Errors.\n","htmlwidgets":"<div id=\"htmlwidget_container\">\n <div id=\"htmlwidget-253801b69b5b14a83fb6\" class=\"formattable_widget html-widget\" style=\"width:100%;height:500px;\" width=\"100%\" height=\"500\"></div>\n</div>\n<script type=\"application/json\" data-for=\"htmlwidget-253801b69b5b14a83fb6\">{\"x\":{\"html\":\"<table class = \\\"table table-condensed\\\"style = \\\"margin:0; border-bottom: 2px solid; border-top: 2px solid; font-size:90%;\\\">\\n<h3 class=\\\".h3\\\" style=\\\"color:#3E7DCC; text-align:left; margin-top:0px; margin-bottom:0\\\">Linear Regression: Q13 Total Spend<\\/h3>\\n<caption style=\\\"caption-side:bottom;font-style:italic; font-size:90%;\\\">n = 1,265 cases used in estimation of a total sample size of 4,853; cases containing missing values have been excluded; R-squared: 0.05681; Correct predictions: 17%; AIC: 10,155; multiple comparisons correction: None<\\/caption>\\n <thead>\\n <tr>\\n <th style=\\\"text-align:left;\\\"> <\\/th>\\n <th style=\\\"text-align:right;\\\"> Estimate <\\/th>\\n <th style=\\\"text-align:right;\\\"> Standard Error <\\/th>\\n <th style=\\\"text-align:right;\\\"> <span style='font-style:italic;'>t<\\/span> <\\/th>\\n <th style=\\\"text-align:right;\\\"> <span style='font-style:italic;'>p<\\/span> <\\/th>\\n <\\/tr>\\n <\\/thead>\\n<tbody>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> (Intercept) <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"color:blue\\\">15.67<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.98 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; font-weight: bold; background-color: #80b4f4\\\">7.93<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"font-weight: bold\\\">&lt; .001<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 19 to 24 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>-0.93<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.54 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; background-color: #fef1ef\\\">-0.60<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>.546<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 25 to 29 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>2.50<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.88 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; background-color: #ddebfc\\\">1.33<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>.184<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 30 to 34 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>3.34<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.81 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; background-color: #d0e3fa\\\">1.85<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span>.065<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 35 to 39 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"color:blue\\\">4.64<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.81 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; font-weight: bold; background-color: #bdd8f9\\\">2.56<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"font-weight: bold\\\">.010<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 40 to 44 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"color:blue\\\">6.25<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.80 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; font-weight: bold; background-color: #a6caf7\\\">3.48<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"font-weight: bold\\\">&lt; .001<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; text-align:left;\\\"> S1 Age: 45 to 49 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"color:blue\\\">4.02<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> 1.83 <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"display: block; padding: 0 4px; border-radius: 4px; font-weight: bold; background-color: #c7ddfa\\\">2.20<\\/span> <\\/td>\\n <td style=\\\"vertical-align:middle; text-align:right;\\\"> <span style=\\\"font-weight: bold\\\">.028<\\/span> <\\/td>\\n <\\/tr>\\n <tr>\\n <td style=\\\"vertical-align:middle; 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