1. Data Classification – Identifying types of data (qualitative, discrete quantitative, continuous quantitative) based on a sports coach′s session data. 2. Probability and Events – Calculating probabilities for selecting random nests or birds and analyzing data from two sections of a forest study. 3. Statistical Analysis – Using mean, standard deviation, and other statistics to evaluate sprinter performances, and calculating seasonal components for company profits. 4. Sampling Techniques – Exploring systematic and stratified sampling methods, including advantages, disadvantages, and sample representation. 5. Cumulative Frequency and Interpolation – Completing tables and estimating values using linear interpolation in various contexts, such as sea cucumbers and employee surveys. 6. Survey Design and Sampling – Analyzing open-ended questions, advantages, and disadvantages of surveying populations versus samples.