U.S. Department of Labor Employment and Training Administration 1 Data Mining Using the Federal Research and Evaluation Database Describe Explain Predict

2 Agenda Overview of the toolOverview of the tool The basics of data analysisThe basics of data analysis TAA and WIA application menusTAA and WIA application menus Exploring menu optionsExploring menu options Example scenariosExample scenarios Questions?Questions?

3 Overview of the Tool The Federal Research and Evaluation Database (FRED) enables analysis of the Trade Act Participant Report (TAPR) and the WIA Standardized Record Data (WIASRD). Both are annually submitted by states on exiters' demographic characteristics, the services they received, and the outcomes they achieved after exit. Currently contains data on exiters from the PY04 WIASRD and FY05 TAPRCurrently contains data on exiters from the PY04 WIASRD and FY05 TAPR Examine performance, caseload and program information from the national, regional, state and local levelsExamine performance, caseload and program information from the national, regional, state and local levels Display trends in performance by quarter as well as the characteristics of the exiter cohortDisplay trends in performance by quarter as well as the characteristics of the exiter cohort Create comparison groups based on parameters set by the userCreate comparison groups based on parameters set by the user Create cross-tabulation tables and correlationsCreate cross-tabulation tables and correlations

4 Data Elements or Variables Dependent variable (end-result or outcome)Dependent variable (end-result or outcome) Independent variables (causal or predictor)Independent variables (causal or predictor) Control or intervening variables (confounding)Control or intervening variables (confounding) Types of variables (levels of measures)Types of variables (levels of measures) –Nominal –Ordinal –Interval –Ratio Remember: The types of variables we choose determines the statistical procedures we use in the analyses. CategoricalScale The Use of Data Elements in FRED

5 Descriptive Statistics Summary statistics on key variables –Number, mean, minimum, maximum, standard deviation, percentiles Graphical techniques are often used to display distributions Cross-tabulations are used to describe the relationships between two or more variables

6 Go to Application Menus

7 Accessing the WIA Menu

8 Program Area Specific Funding Formula Specific Accessing the WIA Menu

9 14 Applications WIA Program-Specific Menu

10 Accessing the TAA Menu

11 10 Applications Accessing the TAA Menu

12 Drill down-all measures Drill down-all measures Drill down by measure Drill down by measure Benchmark performance against peers Benchmark performance against peers Create a performance adjustment model and worksheet Create a performance adjustment model and worksheet Calculated performance by rolling quarters Calculated performance by rolling quarters Profiles by program area Profiles by program area Find the top performers for a given performance measure Find the top performers for a given performance measure Ad hoc analysis Ad hoc analysis Commonly Used Menu Options

13 This tool allows the user to drill down into program year and levels of program administration to examine performance. The All Measures selection allows the user to examine performance for all measurement groups at once. Drill Down: All Measures

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20 Focusing on a single measure at a time, this tool allows the user to drill down into program year and levels of program administration to examine performance. The By Measures selection allows the user to examine the effect of client characteristics and program services on a performance outcome. Drill Down: By Measures

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28 Downloaded file is in a comma separated value (CSV) format

29 This tool allows the user to benchmark the performance of a given state or local area against the performance of other areas with similar conditions. Benchmark Performance

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35 This tool allows the user to develop a performance adjustment model to help in understanding the impacts of various factors on performance at the state, regional or national level. The model is displayed as a worksheet. The user can adjust the factors included in the worksheet on-line to explore the impacts resulting from changes in customer characteristics, program services, and economic conditions. Adjustment Model

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40 This link provides detailed results from the regression procedure, including correlation coefficients.

41 This tool allows the user to analyze performance trends that reflect a four quarter average. Looking at a year’s worth of data each quarter removes cyclical quarter to quarter fluctuations to more clearly see overall performance trends. Performance by Rolling Quarters

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46 This tool allows the user to display customer and program service profiles by funding stream during a given program year. Profiles may also be created to reflect national, regional, state or LWIA characteristics. Area Profiles

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51 This tool allows the user to display the top performing state or local area for a given performance measure and a specific customer characteristic. Top Performers

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56 This tool allows the user to choose the combination of variables of interest to create and display cross-tabulation tables. The user can also display the results by a third variable of interest. Ad Hoc Analysis

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61 ETA’s Performance and Results Web Page ETA’s Administrative Data Research and Evaluation (ADARE) Project Website For More Information