Global Certificate in Homelessness Research: Data Analysis Techniques
-- ViewingNowThe Global Certificate in Homelessness Research: Data Analysis Techniques is a comprehensive course designed to equip learners with essential skills in data analysis for homelessness research. This course is crucial in today's world where there is a growing need for professionals who can analyze complex data sets to inform policies and strategies to address homelessness.
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โข Data Collection Techniques: Understanding the various methods for collecting data on homelessness, including surveys, interviews, and administrative records. โข Data Cleaning and Pre-processing: Techniques for cleaning and preparing homelessness data for analysis, including handling missing data and outliers. โข Descriptive Statistics: Overview of statistical methods for summarizing and visualizing homelessness data, including measures of central tendency and dispersion. โข Inferential Statistics: Introduction to statistical methods for making inferences about homelessness populations, including hypothesis testing and confidence intervals. โข Regression Analysis: Overview of regression models for analyzing the relationships between variables in homelessness research, including linear and logistic regression. โข Multivariate Analysis: Techniques for analyzing homelessness data with multiple variables, including factor analysis and cluster analysis. โข Spatial Analysis: Methods for analyzing homelessness data that take into account the geographic context, including spatial autocorrelation and spatial regression. โข Data Visualization: Techniques for effectively communicating homelessness research findings through data visualization, including charts, graphs, and maps. โข Ethical Considerations: Discussion of ethical issues that arise in homelessness research, including informed consent, confidentiality, and data security.
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