Recommended Learning Path
- Descriptive Statistics: Learn measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation).
- Probability Basics: Understand probability theories, distributions, and real-world applications.
- Inferential Statistics: Study hypothesis testing, confidence intervals, and p-values.
- Correlation & Regression: Learn methods to assess relationships between variables.
- Advanced Techniques: Master methods like ANOVA for comparing groups and chi-square tests for categorical data analysis.
- Sampling Methods: Study methods like random and stratified sampling to ensure representative data.
Common Methods
- Mean, Median, Mode: Understand data distribution.
- Standard Deviation & Variance: Measure data spread and variability.
- Linear Regression: Model and predict relationships between variables.
- Hypothesis Testing: Assess assumptions and validate outcomes.
- Chi-Square Tests: Evaluate relationships between categorical variables.
- ANOVA: Compare means among multiple groups to determine significant differences.
Resources