Data Collection Methods

To gather data that already exists and can be used to answer research questions or solve problems.

Stock variables are measured at a specific point in time, while flow variables are measured over a period of time.

To organize data in a consistent and structured format, making it easier to analyze and visualize.

<p>The process of identifying and resolving duplicate or ambiguous records in a dataset.</p> Signup and view all the answers

<p>To explore and understand the structure and characteristics of a dataset, and to identify patterns and relationships.</p> Signup and view all the answers

<p>Surveys involve collecting data from a specific group of people, while sampling involves selecting a subset of data from a larger population.</p> Signup and view all the answers

<p>To identify and correct errors, inconsistencies, and inaccuracies in a dataset, making it ready for analysis.</p> Signup and view all the answers

<p>To ensure reproducibility and transparency of the data analysis process, and to facilitate collaboration and communication.</p> Signup and view all the answers

<p>Data exploration is the initial step in analyzing a dataset, involving the identification of patterns, relationships, and anomalies to understand the characteristics of the data. It is essential because it helps in identifying issues with the data, understanding the underlying structure, and guiding the subsequent analysis.</p> Signup and view all the answers

<p>The primary goals of data exploration are to understand the data distribution, identify outliers and anomalies, and reveal relationships between variables. These goals contribute to the overall analysis by providing a solid foundation for subsequent statistical modeling and inference.</p> Signup and view all the answers

<p>Data preparation involves cleaning, transforming, and formatting the data to make it suitable for analysis. It is essential because it ensures that the data is in a usable state, which is crucial for accurate exploration and subsequent analysis.</p> Signup and view all the answers

<p>Data exploration facilitates the identification of relationships between variables through visualizations and statistical summaries. These relationships can indicate correlations, patterns, or causal links, which have significant implications for understanding the underlying phenomena and making predictions.</p> Signup and view all the answers

<p>Comparing and correlating data variables helps in identifying relationships, patterns, and anomalies, which can inform the selection of statistical models and the interpretation of results.</p> Signup and view all the answers

<p>Data exploration contributes to the development of hypotheses by identifying patterns, relationships, and anomalies, which guide the formulation of hypotheses. These hypotheses can then be tested using statistical methods to establish their validity.</p> Signup and view all the answers

<p>To facilitate many kinds of data analysis</p> Signup and view all the answers

<p>The World Bank</p> Signup and view all the answers

<p>FRED is a collection of economic time series data on the USA and some other countries, collected and stored by the US Federal Reserve system.</p> Signup and view all the answers

<p>Using an Application Programming Interface (API)</p> Signup and view all the answers

<p>Information on the web and administrative data</p> Signup and view all the answers

<p>Big Data</p> Signup and view all the answers

<p>It allows data analysts to directly load data into statistical software</p> Signup and view all the answers

<p>They provide free and readily available data for analysis</p> Signup and view all the answers