• Machine Learning Introduction: Types of data, frequency distribution, data representation, probability, central limit theorem, sampling types, descriptive statistics, inferential statistics
• Descriptive Statistics (central tendency /variance)
• Frequency Tables / Summarization
• Hypothesis Testing- t-tests/z-test (1-sample, independent sample, paired sample)
• Analysis of Variance (ANOVA)
• Correlations/chi-square test