Data Processing Lab: Handling Missing Data
This spreadsheet simulation teaches learners how to handle missing data by combining temperature data visualization with hands-on practice with different imputation methods. It’s ideal for students looking to improve their spreadsheet skills, offering step-by-step instructions along with built-in hints and feedback.
Topics
- Data science
- data literacy
- high school
- next generation science standards
- NGSS
- imputation
- row deletion
- mean imputation
- linear interpolation
- multiple imputation
- constant value imputation
- zero imputation
- missing data
- missing values
- data gaps
- data cleaning
- bias
- spreadsheet
- cells
- rows
- columns
- formula
- function
- ISBLANK
- AVERAGE
- MEDIAN
- NORMINV
- RAND
- fill handle
- time series data
- summary statistics
- data visualizations
- statistical models
- uncertainty
- variability
- data preparation
- temperature data
- monthly mean temperatures
- environmental science