AP Statistics
AP Statistics is a high school-level course that introduces students to the principles and methods of statistics.
90%
of students score
4 and above
78%
students get a top score of
5 in
AP Statistics
80%
students showed exceptional
performance in their first semester of
AP Statistics
Course Concept
AP Statistics is a high school-level course that introduces students to the principles and methods of statistics. It focuses on developing statistical literacy, analytical thinking, and problem-solving skills through the exploration of real-world data.
The course covers a wide range of topics, including data analysis, probability, experimental design, and statistical inference. Students learn how to collect, organize, and analyze data using various statistical techniques and tools. They also learn to interpret and draw conclusions from data, make predictions, and communicate their findings effectively. It is divided in:
- Exploring Data: Students learn how to describe and summarize data using graphical displays, numerical measures, and summary statistics. They analyze patterns and trends in data and develop skills in data visualization and interpretation.
- Sampling and Experimentation: The course covers the principles of sampling and experimental design. Students learn about different sampling methods and experimental designs, and they explore concepts such as randomization, bias, and confounding variables.
- Probability: AP Statistics introduces students to the principles of probability and its application in statistical analysis. They learn about basic probability rules, conditional probability, and probability distributions. Students also study concepts such as expected value, variance, and the law of large numbers.
- Statistical Inference: The course focuses on statistical inference, which involves drawing conclusions and making predictions based on sample data. Students learn about confidence intervals, hypothesis testing, and the use of p-values. They also explore different types of errors and the concept of statistical power.
- Regression Analysis: AP Statistics covers linear regression analysis, where students learn how to model relationships between variables and make predictions based on the regression equation. They study concepts such as correlation, least squares regression, and residuals.
- Probability Models: The course introduces students to probability models, including discrete and continuous probability distributions. They learn about the binomial, geometric, and normal distributions, and how to apply these models to analyze real-world data.
- Experimental Design: AP Statistics emphasizes the importance of experimental design and the principles of controlled experiments. Students learn about factors, levels, randomization, and replication. They also explore observational studies and the challenges of drawing causal conclusions from non-experimental data.
AP Statistics
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COURSE SYLLABUS PDF- Introducing Statistics : What Can We Learn From The Data
- The Language Of Variation: Variables
- Representing a Categorical Variable with Tables
- Representing a Categorical Variable with Graphs
- Representing a Quantitative Variable with Graphs
- Describing the Distribution of a Quantitative variable
- Summary Statistics for a Quantitative Variable
- Graphical Representation of Summary Statistics
- Graphical Representations of Quantitative Variable
- The Normal Distribution
- Introducing Statistics: Are Variables Related ?
- Representing Two Categorical Variables
- Statistics of Two Categorical Variables
- Representing the Relationship between two Quantitative Variables
- Correlation
- Linear Regression Models
- Residuals
- Least Squares Regression
- Analyzing Departures from Linearity
- Introducing Statistics : Do the Data We Collected Tell the Truth?
- Introduction to Planning a Study ,
- Random Sampling and Data Collection
- Potential Problems with Sampling
- Introduction to Experimental Design
- Selecting an Experimental Design
- Inference and Experiments
- Introducing Statistics: Random and Non Random Patterns?
- Estimating Probabilities Using Simulation
- Introduction to Probability
- Mutually Exclusive Events
- Conditional Probability
- Independent Events and Unions of Events
- Introduction to Random Variables and Probability Distributions
- Mean and Standard Deviation of Random Variables
- Combining random Variables
- Introduction to Binomial Distribution
- Parameters of Binomial Distribution
- The Geometric Distribution
- Introducing Statistics : Why is My Sample Not Like Yours
- The Normal Distribution , Revisited
- The Central Limit Theorem
- Biased and Unbiased Point Estimates
- Sampling Distribution for Sample Proportions
- Sampling Distribution for Differences in Sample Proportions
- Sampling Distributions for Sample Means
- Sampling Distribution for Differences In Sample Means
- Introducing Statistics : Why Be Normal?
- Constructing a Confidence Interval for a Population.
- Justifying a Claim based on a Confidence Interval for a Population Proportion.
- Setting Up a Test for a Population Proportion
- Interpreting p- values
- Concluding a Test for a Population Proportion.
- Potential Errors When Performing Tests
- Confidence Intervals for the Difference of Two Proportions
- Justifying a Claim Based on a Confidence Based on a Confidence Interval for a Difference of Population Proportions
- Setting Up a Test for the difference of Two Population Proportion
- Carrying Out a Test for the Difference of Two Population Proportions
- Introducing Statistics : Why Should I Worry About Error?
- Constructing a Confidence Interval for a Population Mean
- Justifying a Claim About a Population Mean Based on a Confidence Interval.
- Setting Up a Test for a Population Mean
- Carrying Out a Test for Population mean
- Confidence Intervals for the Difference of Two Means
- Justifying a Claim About the Difference of Two Means Based on a Confidence Interval
- Setting Up a Test for the Difference of Two Population Means
- Carrying out a Test for the difference of two Population Mean
- Introducing Statistics : Are My Results unexpected?
- Setting up Chi- Square Goodness of Fit Test
- Carrying Out up Chi- Square Goodness of Fit Test
- Expected Counts in Two -Way Tables
- Setting Up Chi- Square Test For homogeneity or Independence
- Carrying Out Chi - Square Test For homogeneity or Independence
- Introducing Statistics : Do Those Points Align?
- Confidence Intervals for the Slopes of Regression Models
- Justifying a Claim About the Slope of a Regression Model Based on a Confidence
- Setting Up a Test for the slope of Regression Models
- Carrying Out a Test for the Slope of a Regression Model
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Complete Application
Step 1 of the APGuru process is the application phase. We'll ask for basic information such as your name, contact details, current educational level, and your specific goals or challenges. Once you've filled out the application, click the submit button. Your application will be promptly reviewed by our admissions team.
Take a Trial Class
Step 2 is the trial class, where applicants receive an invitation to experience our teaching methods and interact with instructors. During this session, students engage in discussions, ask questions, and evaluate whether APGuru aligns with their learning preferences and goals, helping them make an informed decision.
Join AP Guru
Step 3 of the APGuru process involves officially joining the program after a successful trial class. Students confirm their enrollment, select their desired course or program, and gain access to comprehensive study resources. They begin attending regular classes, receiving guidance from experienced instructors, and tracking their progress towards academic excellence.