Math- O level – Statistics and probability
Course Intro
- Learn data analysis, statistics, and probability according to Secondary 4 / O level MOE syllabus.
- Plunge into the world of numbers, distributions, and predictions.
- Sharpen your statistical skills for your O-level academic success.
Course Description
Explore the fascinating world of statistics and probability through engaging live lessons and practical examples. Gain a deep understanding of concepts like quartiles, percentiles, standard deviation, and more. Learn how to analyze data, create visual representations, and make informed decisions based on statistical insights.
Who is this Course for?
Secondary 4 students looking to excel in statistics and probability O-level students interested in mastering data analysis and predictive modeling.
What you will Learn?
- Quartiles, percentiles, and their real-world applications
- Analyzing data using range, interquartile range, and standard deviation
- Creating cumulative frequency diagrams and interpreting their significance
- Box-and-whisker plots for data visualization
- Various statistical representations are needed for effective communication.
Key Takeaways
- Proficiency in statistical analysis and probability calculations
- Ability to interpret and visualize data with confidence.
- Skills to compare data sets using mean and standard deviation.
- Expertise in probability calculations for combined and independent events.
Why Learn from doerdo Tuition Course?
Experienced Teachers: Our courses are taught by experienced ex-MOE educators through Live Interactive Classes.
Detailed Student Insights: Get a clear understanding of your performance and areas for improvement.
Immediate After-Class Support: Our teachers are readily available to address your questions.
AI-Enhanced Homework: Benefit from AI-powered assignments for hands-on practice.
Personalized Learning: Tailored content and mentorship to help you succeed.
Course Curriculum
| Quartiles and Percentiles – Understanding quartiles and their use in data analysis. Example: Calculating quartiles for a dataset of exam scores. Percentiles work similarly, indicating the percentage of data below a specific point. |
| Range, Interquartile Range, and Standard Deviation –The range shows the difference between the highest and lowest values in a dataset. For instance, in the dataset [12, 18, 25, 30, 42], the range is 42 – 12 = 30. The interquartile range (IQR) is the difference between the third quartile (Q3) and the first quartile (Q1). In the same dataset, IQR = Q3 – Q1 = 30 – 18 = 12. Standard deviation measures the dispersion of data points. A high standard deviation indicates greater variability. |
| Cumulative Frequency Diagrams – Analyzing data distribution with cumulative frequency diagrams. Example: Interpreting a cumulative frequency diagram for exam scores. |
| Box-and-Whisker Plots – Visualizing data distribution using box-and-whisker plots. Example: Identifying outliers in a dataset. |
| Types of Statistical Representations – Comparing various statistical representations. Example: Choosing the right chart for displaying data. |
| Standard Deviation Calculation – Calculating standard deviation for grouped and ungrouped data. Example: Finding the standard deviation for a set of measurements. |
| Comparing Two Sets of Data – Using mean and standard deviation to compare data sets. Example: Comparing the performance of two groups using statistics. |
| Probability of Combined Events – Predicting combined events’ probabilities. Example: Calculating the probability of multiple outcomes. |
| Addition and Multiplication of Probabilities – Applying probability rules for mutually exclusive and independent events. Example: Solving probability problems using addition and multiplication rules. |
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Learn from doerTeachers
Young Wai Keong Vincent
Mary Lin An Chin
Suriawati Binte Sulaimi
Tan Qianru
Yee Hong Ng
