Course Modules

Getting Started

Getting Started Getting Started

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Start Here Start Here 1

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Meet Your Instructor Meet Your Instructor 2

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Course Syllabus Course Syllabus 3

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Navigating Canvas Navigating Canvas 4

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Technical Requirements Technical Requirements 5

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Community Guidelines & Academic Integrity Community Guidelines & Academic Integrity 6

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Resources + Support Resources + Support 7

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Module One : Theories, Hypotheses, and Variables

Module One : Theories, Hypotheses, and Variables Module One : Theories, Hypotheses, and Variables

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Module 1: Learning Objectives and Lecture Slides Module 1: Learning Objectives and Lecture Slides 1

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1.1 Getting to know your instructor [5:17] 1.1 Getting to know your instructor [5:17] 3

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1.2 Course Format [5:13] 1.2 Course Format [5:13] 4

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1.3 Grading and Assignments [6:04] 1.3 Grading and Assignments [6:04] 5

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1.4 Course Schedule [12:23] 1.4 Course Schedule [12:23] 6

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1.5 Building Blocks [7:08] 1.5 Building Blocks [7:08] 7

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1.6 Research Questions, Theories, and Hypotheses [11:15] 1.6 Research Questions, Theories, and Hypotheses [11:15] 8

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1.7 Dependent and Independent Variables [9:22] 1.7 Dependent and Independent Variables [9:22] 9

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1.8 The Unit of Analysis [5:27] 1.8 The Unit of Analysis [5:27] 10

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1.9 Types of Variables [8:12] 1.9 Types of Variables [8:12] 11

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1.10 Getting Acquainted With Excel [15:09] 1.10 Getting Acquainted With Excel [15:09] 12

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1.11 Time Management Tips [9:18] 1.11 Time Management Tips [9:18] 13

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Quiz

Quiz 1 Quiz 1 7 14

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Module Two: Descriptive Analysis

Module Two: Descriptive Analysis Module Two: Descriptive Analysis

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Module 2: Learning Objectives and Lecture Slides Module 2: Learning Objectives and Lecture Slides 1

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2.1 What is Descriptive Analysis? [03:40] 2.1 What is Descriptive Analysis? [03:40] 5

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2.2 Univariate Analysis, Part I [05:28] 2.2 Univariate Analysis, Part I [05:28] 6

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2.3 Univariate Analysis, Part II [04:40] 2.3 Univariate Analysis, Part II [04:40] 7

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2.4 Bivariate Analysis with Data Visualization [15:10] 2.4 Bivariate Analysis with Data Visualization [15:10] 8

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2.5 Descriptive Analysis with Excel: Getting Started [17:10] 2.5 Descriptive Analysis with Excel: Getting Started [17:10] 9

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2.6 Univariate Analysis in Excel [14:33] 2.6 Univariate Analysis in Excel [14:33] 10

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2.7 COUNTIF, AVERAGEIF, and VLOOKUP [18:11] 2.7 COUNTIF, AVERAGEIF, and VLOOKUP [18:11] 11

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2.8 Bivariate Analysis with Graphs in Excel [14:17] 2.8 Bivariate Analysis with Graphs in Excel [14:17] 12

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Assignment

Homework 1 Homework 1 100 13

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Module Three : Getting Started with Stata + Populations and Samples

Module Three : Getting Started with Stata + Populations and Samples Module Three : Getting Started with Stata + Populations and Samples

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Module 3: Learning Objectives and Lecture Slides Module 3: Learning Objectives and Lecture Slides 1

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3.1 Introduction [03:19] 3.1 Introduction [03:19] 5

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3.2 Univariate Analysis with Data Visualization [12:15] 3.2 Univariate Analysis with Data Visualization [12:15] 6

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3.3 Bivariate Analysis with Tables and Bar Plots [12:14] 3.3 Bivariate Analysis with Tables and Bar Plots [12:14] 7

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3.4 Bivariate Analysis with Scatter Plots and Correlation Coefficients [17:32] 3.4 Bivariate Analysis with Scatter Plots and Correlation Coefficients [17:32] 8

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3.5 Introduction to Stata [09:56] 3.5 Introduction to Stata [09:56] 9

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3.6 Working with Do Files in Stata [16:59] 3.6 Working with Do Files in Stata [16:59] 10

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3.7 Manipulating Variables and Labels [22:32] 3.7 Manipulating Variables and Labels [22:32] 11

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3.8 Descriptive Analysis in Stata [10:12] 3.8 Descriptive Analysis in Stata [10:12] 12

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3.9 Populations and Samples [09:03] 3.9 Populations and Samples [09:03] 13

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3.10 Margin of Error [04:37] 3.10 Margin of Error [04:37] 14

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Quiz

Quiz 2 Quiz 2 5 15

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Module Four: Hypothesis Testing

Module Four: Hypothesis Testing Module Four: Hypothesis Testing

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Module 4: Learning Objectives and Lecture Slides Module 4: Learning Objectives and Lecture Slides 1

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4.1 Introduction [3:14] 4.1 Introduction [3:14] 5

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4.2 Review: Populations, Samples, and Margins of Error [6:35] 4.2 Review: Populations, Samples, and Margins of Error [6:35] 6

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4.3 The Margin of Error and the Confidence Interval [14:11] 4.3 The Margin of Error and the Confidence Interval [14:11] 7

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4.4 Margins of Error, Confidence Intervals, and Hypothesis Tests [7:12] 4.4 Margins of Error, Confidence Intervals, and Hypothesis Tests [7:12] 8

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4.5 Data Sets, Codebook, and Weights [12:17] 4.5 Data Sets, Codebook, and Weights [12:17] 9

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4.6 Difference in Proportions Test in Stata [22:18] 4.6 Difference in Proportions Test in Stata [22:18] 10

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Quiz

Quiz 3 Quiz 3 5 11

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Module Five : Regression Analysis

Module Five : Regression Analysis Module Five : Regression Analysis

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Module 5: Learning Objectives and Lecture Slides Module 5: Learning Objectives and Lecture Slides 1

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5.1 Introduction [5:38] 5.1 Introduction [5:38] 5

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5.2 Review: Margin of Error, Confidence Intervals, and Hypothesis Testing [4:19] 5.2 Review: Margin of Error, Confidence Intervals, and Hypothesis Testing [4:19] 7

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5.3 P-values and Hypothesis Testing [10:13] 5.3 P-values and Hypothesis Testing [10:13] 8

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5.4 Significance Levels and Hypothesis Testing [15:33] 5.4 Significance Levels and Hypothesis Testing [15:33] 9

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5.5 Regression Analysis: Introduction [9:17] 5.5 Regression Analysis: Introduction [9:17] 10

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5.6 Regression Analysis: From the Data to the Equation [12:44] 5.6 Regression Analysis: From the Data to the Equation [12:44] 11

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5.7 Regression Analysis and Hypothesis Testing [15:13] 5.7 Regression Analysis and Hypothesis Testing [15:13] 12

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5.8 The R-Squared [11:30] 5.8 The R-Squared [11:30] 13

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5.9 Regression Analysis in Stata [4:13] 5.9 Regression Analysis in Stata [4:13] 14

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Assignment

Homework 2 Homework 2 100 15

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Module Six: Introduction to R

Module Six: Introduction to R Module Six: Introduction to R

Page

Module 6: Learning Objectives, Lecture Slides, and R Script Module 6: Learning Objectives, Lecture Slides, and R Script 1

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Page

6.1 Introduction [9:01] 6.1 Introduction [9:01] 2

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6.2 The RStudio Interface [7:44] 6.2 The RStudio Interface [7:44] 3

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6.3 Getting Started with R [13:59] 6.3 Getting Started with R [13:59] 4

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6.4 Vectors [11:59] 6.4 Vectors [11:59] 5

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6.5 Subsetting Vectors [14:11] 6.5 Subsetting Vectors [14:11] 6

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6.6 Logical Statements [9:15] 6.6 Logical Statements [9:15] 7

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6.7 Matrices and Data Frames [10:07] 6.7 Matrices and Data Frames [10:07] 8

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6.8 Looking at Data [14:08] 6.8 Looking at Data [14:08] 9

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6.9 Introduction to Data Visualization with GGPlot [14:06] 6.9 Introduction to Data Visualization with GGPlot [14:06] 10

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6.10 Criteria of Confounding Variables [7:52] 6.10 Criteria of Confounding Variables [7:52] 11

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6.11 Confounding Vs. Intervening Variables [4:56] 6.11 Confounding Vs. Intervening Variables [4:56] 12

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Quiz

Quiz 4 Quiz 4 5 13

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Module Seven: Cleaning and Visualizing Data in R

Module Seven: Cleaning and Visualizing Data in R Module Seven: Cleaning and Visualizing Data in R

Page

Module 7: Learning Objectives, Lecture Slides, and R Script Module 7: Learning Objectives, Lecture Slides, and R Script 1

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Page

7.1 Introduction [7:11] 7.1 Introduction [7:11] 5

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7.2 Reading Data on Your Computer [10:39] 7.2 Reading Data on Your Computer [10:39] 7

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7.3 County-Level Data from Opportunity Insights [7:04] 7.3 County-Level Data from Opportunity Insights [7:04] 8

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7.4 Cleaning Data with Dplyr: Part I [13:34] 7.4 Cleaning Data with Dplyr: Part I [13:34] 9

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7.5 Cleaning Data with Dplyr: Part II [12:31] 7.5 Cleaning Data with Dplyr: Part II [12:31] 10

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7.6 Cleaning Data with Dplyr: Part III [9:41] 7.6 Cleaning Data with Dplyr: Part III [9:41] 11

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7.7 Histograms and Bar Plots in GGPlot [11:19] 7.7 Histograms and Bar Plots in GGPlot [11:19] 12

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7.8 Facets in GGPlot [20:57] 7.8 Facets in GGPlot [20:57] 13

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7.9 Experiments and the Gold Standard [10:06] 7.9 Experiments and the Gold Standard [10:06] 15

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7.10 Observational Research Design [10:34] 7.10 Observational Research Design [10:34] 16

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Quiz

Quiz 5 Quiz 5 5 21

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Module Eight: Multivariate Regression, Part I

Module Eight: Multivariate Regression, Part I Module Eight: Multivariate Regression, Part I

Page

Module 8: Learning Objectives, Lecture Slides, and R Script Module 8: Learning Objectives, Lecture Slides, and R Script 1

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8.1 Introduction [4:12] 8.1 Introduction [4:12] 6

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8.2 Review: Regression Analysis [7:41] 8.2 Review: Regression Analysis [7:41] 8

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8.3 Multivariate Regression: Introduction [11:26] 8.3 Multivariate Regression: Introduction [11:26] 9

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8.4 Multivariate Regression and Confounding Variables [13:02] 8.4 Multivariate Regression and Confounding Variables [13:02] 10

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8.5 Multivariate Regression in R [22:22] 8.5 Multivariate Regression in R [22:22] 11

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8.6 Interpreting Regressions With Logarithmic Transformations [8:32] 8.6 Interpreting Regressions With Logarithmic Transformations [8:32] 12

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8.7 Importing and Combining Data in R [16:40] 8.7 Importing and Combining Data in R [16:40] 13

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Assignment

Homework 3 Homework 3 100 14

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Module Nine: Multivariate Regression, Part II

Module Nine: Multivariate Regression, Part II Module Nine: Multivariate Regression, Part II

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Module 9: Learning Objectives, Lecture Slides, and R Script Module 9: Learning Objectives, Lecture Slides, and R Script 1

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9.1 Introduction [8:32] 9.1 Introduction [8:32] 3

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9.2 The Standard Error of the Regression Slope, Part I [9:49] 9.2 The Standard Error of the Regression Slope, Part I [9:49] 4

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9.3 The Standard Error of the Regression Slope, Part II [10:53] 9.3 The Standard Error of the Regression Slope, Part II [10:53] 6

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9.4 Reading Regression Tables [12:03] 9.4 Reading Regression Tables [12:03] 7

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9.5 Review: Multivariate Regression and Confounds [19:56] 9.5 Review: Multivariate Regression and Confounds [19:56] 8

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9.6 Recoding in R, Part I [9:28] 9.6 Recoding in R, Part I [9:28] 9

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9.7 Recoding in R, Part II [12:20] 9.7 Recoding in R, Part II [12:20] 10

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Assignment

Final Project Final Project 100 11

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Module Ten: Dummy Variables

Module Ten: Dummy Variables Module Ten: Dummy Variables

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Module 10: Learning Objectives, Lecture Slides, and R Script Module 10: Learning Objectives, Lecture Slides, and R Script 1

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10.1 Introduction [4:26] 10.1 Introduction [4:26] 2

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10.2 Introduction to Dummy Variables [05:24] 10.2 Introduction to Dummy Variables [05:24] 3

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10.3 Dummy Variables in Regressions [8:44] 10.3 Dummy Variables in Regressions [8:44] 4

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10.4 Dummy Variables in R - Part I [6:56] 10.4 Dummy Variables in R - Part I [6:56] 5

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10.5 Dummy Variables in R - Part II [9:43] 10.5 Dummy Variables in R - Part II [9:43] 6

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10.6 Dummy Variables in R - Part III [12:19] 10.6 Dummy Variables in R - Part III [12:19] 7

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10.7 Dummy Variables in R - Part IV [5:33] 10.7 Dummy Variables in R - Part IV [5:33] 8

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10.8 From Stargazer to Word [6:52] 10.8 From Stargazer to Word [6:52] 9

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10.9 Resources to Keep Learning R [6:14] 10.9 Resources to Keep Learning R [6:14] 10

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