Design a Data Collection and Analysis Plan

Design a complete data collection and analysis plan for the following:

Research objective: [what you are trying to find out or prove]
Data type needed: [quantitative / qualitative / mixed]
Data sources available: [surveys / databases / public datasets / experiments / observations / interviews / existing records]
Sample size considerations: [how many data points or participants]
Data collection timeline: [how long you have to collect data]
Analysis tools available: [Excel / Python / R / SPSS / Tableau / other]
Statistical expertise level: [no statistics / basic / intermediate / advanced]
Output needed: [report / dashboard / academic paper / business presentation]

Build the complete plan:

DATA REQUIREMENTS SPECIFICATION:
- Exact variables to collect
- Operational definitions (how each variable is measured)
- Data types (continuous / categorical / ordinal / binary)
- Required precision and accuracy
- Proxy variables where direct measurement is not possible

COLLECTION METHODOLOGY:
- Primary vs secondary data strategy
- Sampling approach (random / stratified / purposive / convenience)
- Sample size calculation with justification
- Data collection instruments (survey / observation form / extraction script)
- Quality control during collection
- Ethical considerations and consent

DATA MANAGEMENT:
- File naming and version control
- Storage and security
- Backup protocol
- Data dictionary template

DATA CLEANING PROCESS:
- Missing data handling strategy
- Outlier identification and treatment
- Data validation checks
- Normalisation or standardisation needs
- Duplicate detection

ANALYSIS PLAN:
- Descriptive statistics to produce first
- Inferential statistical tests appropriate for each research question
- Visualisation types for each finding
- Subgroup analyses planned
- Sensitivity analyses

INTERPRETATION FRAMEWORK:
- What would confirm your hypothesis
- What would challenge it
- How to handle unexpected findings
- Limitations to acknowledge

OUTPUT TEMPLATES:
- Analysis output structure
- How to present each finding type
- Tables and charts needed