Paano ba gumaling sa math?”

This AP course in statistics is designed to introduce students to the major concepts and tools for collecting, analyzing and drawing conclusions from data. Students are exposed to four broad conceptual themes:

- 1. Exploring Data: Describing patterns and departures from patterns
- 2. Sampling and Experimentation: Planning and conducting a study
- 3. Anticipating Patterns: Exploring random phenomena using probability and simulation
- 4. Statistical Inference: Estimating population parameters and testing hypotheses

1.1 Differentiating Categorical Vs Quantitative Variable

1.3 Constructing Stem-and-Leaf Plot (Stem Plot)

* 1.4 Constructing Frequency Distribution Table (FDT) And Ogive

1.5 Measuring Center Of A Distribution

1.6 Measuring Spread, Determining Inter-quartile Range (IQR) and Constructing Box Plot

2.1 Measuring Relative Standing Using Z-Scores

2.2 Using the 68-95-99.7 Rule in Normal Distribution

2.3 Computing for Normal Probability Using the Z-Table

2.4 Computing for Area Under The Curve - Normal Probability Distribution Using Ti84

2.5 Computing for Normal Probability Using Given the Mean and Standard Deviation

3.1 Differentiating Explanatory Vs Response Variable (Scatterplot)

3.3 Interpreting Correlation or the value of "r"

3.4 Writing Linear Model (LSRL) To Predict Outcome

3.5 Generating Linear Model (LSRL) Using Computer Output and Numerical Summary

4.1 Designing Experiments - Population Vs. Statistic

4.2 Designing Experiments - Selection Bias and Lurking Variable vs Confounding Variable

4.3 Randomizing Sample Using Table of Random Numbers or Random Number Generator

4.4 Simulating an Experiment by Using Random Number Generator

5.1 Sample Space & Classical Probability

5.2 Probability Rules (Dependent and Independent Events)

5.4 Conditional Probability Using 2-way Table and General Addition Rule

5.6 Probability Using a Two-way Table, Venn Diagram, and Tree Diagram

6.1 Probability of Discrete Random Variables

6.2 Calculating the Mean and Standard Deviation of a Random Variable

6.3 Verifying and Solving Binomial Probability

6.4 Computing for the Mean and Standard Deviation of a Binomial Distribution

7.1 The Central Limit Theorem (Parameter VS Statistic)

7.2 Computing for the Mean and Standard Deviation of the Mean Sampling Distribution

7.3 Verifying Conditions of the SAMPLE PROPORTION for Normal Approximation

7.4 Computing for the Mean And Standard Deviation of Sample Proportions

8.1 Introduction to Confidence Interval for Population Mean

8.2 Computing for the Confidence Interval for Population Mean

8.3 Computing For The Sample Size to Estimate the Population Mean

8.4 Confidence Interval Using t-distribution for One-Sample Mean (Unknown parameter)

8.6 Computing For Confidence Interval For Population Proportion and Determining Desired Sample Size

8.7 Calculating the Estimation of the Population Parameter on One-Sample Proportion

9.1 Introduction To Hypothesis Testing

9.2 Performing Hypothesis Testing For One-Sample Mean Using Z-test

9.4 Hypothesis Testing for Two-Sample Means

9.5 Interpreting Type I And Type II Errors in Hypothesis Testing

9.6 Performing Hypothesis Testing On One-Sample Proportion

9.7 Performing Hypothesis Testing For Two-Sample Proportions