AP Statistics, DSST, College Stats & Probability 2025 from Udemy

What's inside

Learning objectives

Understand probability and its uses in the real world.

Use advanced statistic techniques.

Understand probability and its uses in the real world.
Use advanced statistic techniques.

Syllabus

Understand Descriptive Statistics, Populations, Samples, Categorical, Discrete and Continuous Data, using Excel and Excel for Statistics.

Make better sense of the use of numbers and data in articles, graphs and charts.

Add to this courses Q&A section as you go through this course. I will try to respond within 24-48 hours to ANY questions and I will record new lectures as needed. We greatly appreciate your positive feedback!

Learn the difference between numerical and categorical data.

Learn how to organize data in pie charts, bar graphs and pareto charts.

Learn how to organize data in stem and leaf charts.

Learn how to organize data in Frequency tables, Histogram charts and Ogive charts.

Learn how to organize data in Contingency Tables, Scatter Plots and Time Series.

Learn how to calculate Mean, Median and Mode.

Learn how to calculate Range, Variance and Standard Deviation.

Learn how to calculate Z scores.

Find out how a sample and population are different.

Understand the use of standard deviations in the Empirical Rule.

Learn how to calculate Quartiles.

Learn how to calculate the five number summary which makes up boxplots.

Learn how to calculate probability.

Find the difference between Mutually Exclusive and Collectively Exhaustive Events

Learn how to calculate marginal and joint probabilities.

Learn how to calculate conditional probabilities.

Learn how to calculate dispersion.

Learn how to calculate combinations and permutations.

Learn how to calculate binomial distrbutions.

Find probabilities in the in the Binomial Distribution table.

Learn how to calculate Poisson Distribution.

Find probabilities in the in the Poisson table.

Learn how to convert X to Z.

Find Z critical values in the Standardized Normal Table.

Learn how to calculate normal probabilities.

Learn how to calculate X for known probabilities.

Learn various types of sampling methods.

Learn how to calculate sample mean distribution.

Find t critical values in the t Critical Value Table.

Learn how to calculate confidence intervals when o is known.

Learn how to calculate confidence intervals when o is unknown.

Learn how to calculate confidence intervals for the p.

Learn how to calculate n or sample size.

BONUS SECTION! No sound for these videos. Everything we would have said we typed into the actual slides. They are video format because Udemy converted out PowerPoints. Thank you and ENJOY!

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Read about what's good

what should give you pause

and possible dealbreakers

Covers descriptive statistics, probability, distributions, sampling, estimation, confidence intervals, hypothesis testing, chi-square distributions, and linear correlation and regression, which are all tested on the AP Statistics exam

Includes instruction on using Excel for statistical analysis, which is a practical skill for both academic and professional settings

Requires a prerequisite of Algebra 1, which may exclude some learners who have not yet reached that level of mathematical understanding

Includes a bonus section with video lectures that do not have sound, which may be a less engaging learning experience for some students

Teaches how to calculate probabilities, combinations, permutations, binomial distributions, and Poisson distributions, which are fundamental concepts in statistics

Explores topics such as hypothesis testing and chi-square distributions, which are essential for making inferences and drawing conclusions from data

Reviews summary

Exam-focused ap and college statistics prep

According to learners, this course is a comprehensive introduction to statistics and probability specifically designed for those preparing for AP Statistics, DSST, or introductory college-level exams. Students highlight the instructor's ability to explain complex topics clearly and the thorough coverage of the syllabus, including descriptive statistics, probability, distributions, confidence intervals, and hypothesis testing. The course structure with lectures and problems is often cited as helpful for understanding concepts and preparing for tests. A notable positive feature mentioned is the instructor's commitment to responding thoughtfully to discussion questions. Some students note that it provides a solid foundation, while others suggest that supplementing with additional practice may be beneficial, depending on individual learning needs and exam requirements.

Instructor is active and helpful in Q&A.

"The instructor responds quickly and thoroughly to questions in the discussion section."

"It's great to have an instructor who is so engaged and willing to help."

"My questions were answered within a day, which was very helpful."

Covers a wide range of essential statistics topics.

"The course content covered everything from basic descriptive stats to inference methods."

"I appreciated the detailed sections on different probability distributions."

"It seems to hit all the major topics required for an introductory statistics course."

Aids preparation for AP, DSST, and college exams.

"This course covered all the topics I needed for my AP Statistics exam."

"I found the practice problems and lecture structure to be very helpful preparation for my college statistics final."

"Using this alongside other materials significantly boosted my confidence for the DSST."

Instructor explains difficult concepts clearly.

"The explanations of complex statistical concepts are very clear and easy to follow."

"I finally understood hypothesis testing after this course; the instructor broke it down simply."

"The lectures made probability much less intimidating than my textbook did."

Bonus videos lack audio, rely on text.

"The bonus section videos don't have sound, which is a bit jarring after the main lectures."

"It's good that the info is in the slides for the bonus content, but no audio makes it harder to follow."

"The note about the bonus videos having no sound is important; be prepared to read the slides."

May need additional practice or resources.

"While the explanations are good, I felt I needed more practice problems, especially for the more advanced topics."

"I used this course as a foundation but also studied from a textbook for extra examples."

"To truly master the concepts for the exam, supplementing with released AP problems was necessary."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in AP Statistics, DSST, College Stats & Probability 2025 with these activities:

Review Algebra 1 Concepts

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Strengthen foundational algebra skills to prepare for the statistical concepts covered in the course.

Browse courses on Algebra

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Review key algebra topics like solving equations and graphing.
Practice algebra problems to build confidence.

Review 'Statistics' by David Freedman, Robert Pisani, and Roger Purves

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Gain a deeper understanding of statistical concepts through a well-regarded introductory textbook.

View Statistics, 4th Edition on Amazon

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Read chapters related to descriptive statistics and probability.
Work through the examples and exercises in the book.

Practice Probability Problems

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Reinforce understanding of probability calculations through repetitive problem-solving.

Browse courses on Probability

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Solve probability problems from textbooks or online resources.
Focus on problems involving conditional and marginal probability.
Check your answers and review the solutions.

Four other activities

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Create a Data Visualization

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Solidify understanding of data representation by creating visualizations using tools like Excel.

Browse courses on Data Visualization

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Choose a dataset related to a topic covered in the course.
Create a bar chart, pie chart, or histogram to visualize the data.
Write a brief description of the visualization and its insights.

Review 'Naked Statistics: Stripping the Dread from the Data' by Charles Wheelan

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Gain a more intuitive understanding of statistics through a non-technical and engaging book.

View Naked Statistics: Stripping the Dread from the... on Amazon

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Read chapters related to topics covered in the course.
Reflect on the real-world examples provided in the book.

Analyze a Real-World Dataset

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Apply statistical techniques to analyze a real-world dataset and draw meaningful conclusions.

Browse courses on Data Analysis

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Find a publicly available dataset of interest.
Formulate a hypothesis to test using the data.
Perform statistical analysis using appropriate techniques.
Write a report summarizing your findings and conclusions.

Tutor a Student in Statistics

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Reinforce your understanding of statistics by explaining concepts to another student.

Browse courses on Statistics

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Find a student who needs help with statistics.
Review the concepts they are struggling with.
Explain the concepts in your own words and answer their questions.

Career center

Learners who complete AP Statistics, DSST, College Stats & Probability 2025 will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians develop and apply statistical theories and methods to collect, analyze, and interpret data to solve real-world problems. This course introduces core statistical principles, including descriptive statistics, probability, random variables, distributions, sampling, estimation, confidence intervals, hypothesis testing, and linear correlation and regression, which are fundamental for a career as a statistician. The advanced statistical techniques taught in this course such as chi-square distributions are also highly relevant. This course helps build a foundation for a career as a statistician who typically has an advanced degree.

See salaries and explore the career path for Statistician

Data Analyst

A data analyst uses statistical methods to analyze data, interpret trends, and provide insights to help organizations make informed decisions. This course teaches fundamental statistical concepts like descriptive statistics, probability, distributions, sampling, estimation, confidence intervals, and hypothesis testing, all of which are essential components of a data analyst's work. Additionally, the use of Excel for statistical analysis, also taught in this course, is a practical tool used by data analysts. Therefore, this course may be useful for anyone aspiring to a data analyst role.

See salaries and explore the career path for Data Analyst

Econometrician

Econometricians use statistical methods to analyze economic data and build models. This role benefits from a strong understanding of statistical inference, correlation, and regression. This course introduces probability, distributions, sampling, and hypothesis testing, all of which are fundamental to econometrics. Furthermore, this course includes instruction on linear regression, which is a central tool for econometricians. Econometricians typically have a master's degree or PhD.

See salaries and explore the career path for Econometrician

Data Scientist

Data scientists extract knowledge and insights from data using advanced analytical approaches. Central to this role is working with statistical techniques. This course lays a foundation using statistical concepts like probability, distributions, sampling, estimation, and hypothesis testing. The course also includes instruction in data visualization, and using Excel for statistical analysis which may be helpful to a data scientist. Furthermore, this course covers linear correlation and regression, a must-have for a data scientist. Data scientists typically have an advanced degree.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative analysts use mathematical and statistical models to analyze financial markets, develop trading strategies, and manage risk. This role relies heavily on statistical approaches. The use of probability distributions, hypothesis testing, and linear regression, all components of this course, are useful to quantitative analysts. This course may be useful to those who want to become a quantitative analyst, a role that often requires a master's degree or PhD.

See salaries and explore the career path for Quantitative Analyst

Business Intelligence Analyst

Business intelligence analysts use data to identify patterns and extract actionable insights that support business decisions. The role requires a strong understanding of statistical analysis techniques. This course may be useful to a business intelligence analyst since it provides instruction in foundational statistical concepts including descriptive statistics, probability distributions, and hypothesis testing, along with data visualization skills. Additionally, the use of Excel for statistical analysis, taught in this course, may be quite helpful to a business intelligence analyst.

See salaries and explore the career path for Business Intelligence Analyst

Epidemiologist

Epidemiologists investigate patterns and causes of disease and health outcomes in populations by analyzing complex datasets. This course helps build a foundation for epidemiologists by providing knowledge of statistical concepts, such as distributions, sampling, and hypothesis testing, that are vital for the accurate interpretation of health data. Specifically, the use of chi-square distributions, taught in this course, may be useful to an epidemiologist. Epidemiologists typically have a master's or doctoral degree.

See salaries and explore the career path for Epidemiologist

Operations Research Analyst

Operations research analysts apply mathematical and statistical techniques to improve the efficiency of business operations. This role utilizes statistical methods to analyze complex systems. This course covers descriptive statistics, probability, distributions, sampling, and linear regression which may be helpful to an operations research analyst when optimizing systems. The use of Excel for statistical analysis, also taught in this course, is a practical skill for an operations research analyst.

See salaries and explore the career path for Operations Research Analyst

Biostatistician

Biostatisticians use statistical methods to address research questions in health and biology. This role requires a strong command of statistical inference and probability. This course provides foundational knowledge in descriptive statistics, probability, distributions, sampling, and hypothesis testing, which may be useful to a biostatistician. This course also covers topics such as chi-square distributions which may be particularly relevant to the field. Biostatisticians typically have a master's or doctoral degree. This course may be useful for those who wish to enter this field.

See salaries and explore the career path for Biostatistician

Survey Statistician

Survey statisticians design and analyze surveys to collect data on populations of interest. A strong understanding of statistical sampling, estimation, and hypothesis testing is critical. This course's coverage of those topics, along with descriptive statistics, would help a survey statistician. This course also teaches about distributions, confidence intervals, and linear regression, all of which may be beneficial in this role.

See salaries and explore the career path for Survey Statistician

Market Research Analyst

Market research analysts study consumer behavior and market trends to advise companies on product development, pricing, and marketing strategies. This role relies on statistical analysis to accurately interpret survey data and identify significant patterns. This course introduces probability, sampling, estimation, and hypothesis testing which helps a market research analyst draw valid conclusions from data. This course also provides practice with descriptive statistics and data visualization techniques such as generating and interpreting charts, which may be useful for a market research analyst.

See salaries and explore the career path for Market Research Analyst

Risk Analyst

Risk analysts assess and quantify potential risks to organizations, using primarily statistical methods. This course introduces core statistical concepts including probability, distributions, sampling, and hypothesis testing, all of which are relevant to understanding risk analysis. The analysis of linear correlation and regression covered in this course may also be useful to a risk analyst. This course may help build the foundation necessary to become a risk analyst.

See salaries and explore the career path for Risk Analyst

Research Assistant

Research assistants support research projects by collecting, organizing, and analyzing data. This role benefits from a thorough understanding of statistical methods, enabling the assistant to help analyze research findings with accuracy. This course covers the essential statistical concepts such as descriptive statistics, probability, distributions, sampling, and hypothesis testing that form the backbone of most research designs. For a person interested in entering the field of research, this course helps build a foundation and may be useful.

See salaries and explore the career path for Research Assistant

Financial Analyst

Financial analysts use statistical models to evaluate financial performance, predict future outcomes, and guide investment decisions. This course provides a solid foundation in statistical concepts, including probability, distributions, sampling, linear correlation and regression, and hypothesis testing, all of which are highly relevant for financial modeling. The understanding of descriptive statistics and data analysis, taught in this course, may be useful for a financial analyst to produce and interpret reports.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries apply statistical and mathematical methods to analyze risk and uncertainty in the insurance and finance industries. This course covers several key statistical concepts like probability, random variables, distributions, and regression. Actuaries use these core statistical principles when making projections about future events. This course helps build understanding of descriptive statistics, which may be helpful in developing reports for the role of an actuary.

See salaries and explore the career path for Actuary

AP Statistics, DSST, College Stats & Probability 2025

What's inside

Learning objectives

Syllabus

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Reviews summary

Exam-focused ap and college statistics prep

Activities

Career center

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