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Data Collection and Design

• Survey and Experiment Design: Develop and design surveys, experiments, and data collection methods to ensure the acquisition of accurate, reliable, and representative data. This includes determining the sample size, sampling methods, and data collection techniques.

• Data Gathering: Oversee or directly participate in the collection of data from various sources, which may include surveys, experiments, administrative records, or databases.

Data Analysis

• Statistical Modeling: Utilize statistical models and methodologies, such as regression analysis, hypothesis testing, and time-series analysis, to interpret complex data and uncover underlying patterns or relationships.

• Data Interpretation: Analyze quantitative data to generate insights, which may involve calculating measures of central tendency, variability, correlation, and conducting inferential statistics to make predictions or decisions.

Data Management

• Data Cleaning: Engage in data cleaning processes, including the identification and correction of errors, handling of missing data, and transformation of variables to ensure the integrity and accuracy of the data set.

• Data Organization: Organize and structure data for analysis, often using statistical software such as R, SAS, SPSS, or Python, ensuring that data is stored and retrieved efficiently.