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Introduction & Data Literature Review The Role of the Private Sector AI and the Labour Market Global studies looking at attitudes towards AI Asymmetries in Information: We fear what we don’t know Biases in datasets Unpacking the ‘public’ in public trust in AI Hypotheses Methods Analysis & Results Simple Bar charts Hypotheses - Results Further analyses: Confidence in Organisations Discussion, Limitations, and Conclusion References Data: revised_AI_dataset.

I. INTRODUCTION Ia. Hypotheses II. DATA & VISUALIZATION IIa. Dataset Identifying Variables Importing, Cleaning, and Manipulating the Dataset IIb. Measurements, Descriptive Stats, and Distributions Descriptive Statistics by Region IIc. Missing Data & Diagnostics Missingness Map Missing Data Pattern Omitting Data IId.

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Introduction, Research Question & Hypotheses Data Dependent Variable Independent Variables Comments Relationships in the Data Omitted Variable Bias Methodology / Model Results Robustness: Eliminating Continuous Aggregated Building Variables Conclusion References: Introduction, Research Question & Hypotheses Of all the devastating effects brought about by the global Covid-19 pandemic in 2020, one positive effect that some home buyers might have been excited for was a drop in rental and purchase prices of housing, following the exodus of people out of global cities like New York.

1. Introduction 2. Research proposition and hypothesis 3. Data and measurements 3.1. Defining the independent and dependent variables 3.2 Corporate Human Rights Peformance CHRB Scores by region and sector Allegations of negative human rights, by region and sector 4.

Introduction Demographic forecasts suggest an increasing need to better understand ethnically diverse societies. The globalized nature of today’s economic value chains, travel and more unfortunate drivers of human mobility send international migration to record levels each year.

$\text{Conflict and crime-Rethinking extortion through rebel governance}$ Extortion and rebels- more than just economic underpinnings? Hypothesis $\text{Introducing the Data}$ Variables of Interest Bivariate relationship between Social Service Provision and Extortion $\text{Models}$ Logistic Regression: Social Service Provision and Extortion Marginal effects Choosing the right model $\text{Conclusion}$ $\text{References}$ $\text{Appendix}$ Conflict and crime - Rethinking extortion through rebel governance Extortion and rebels- more than just economic underpinnings?

1. Introduction 2. Data 3. Methods 4. Results and interpretation 5. Conclusion Data used in this project available at: https://drive.google.com/drive/folders/1kGO7K8C57PY4KkB2xyagqnUouEwFRMnM?usp=sharing Please download all of these folders and save this Rmd file in the same folder in which you save them.

Introduction Data Methods & Models Results Conclusion References Annex Introduction Background Recent estimates suggest that over half the population of South Sudan is facing severe acute food insecurity (South Sudan IPC Technical Working Group 2020).

1. Introduction 2. Data and Visualization 3. Methods 4. Results 4.1 Model results and Diagnostics 4.2 Model Selection 4.3 The Interpretation of the Best Model 5. Conclusion References: 1. Introduction According to WHO，unsafe abortion is one of the important reasons for maternal mortality and morbidity.