Статистика для обработки экспериментов и А/B-тестирования from Coursera

Если Вы боитесь проводить А/В тестирование или не уверены, что сможете правильно посчитать сезонность товаров по представленным данным. Если Вам хочется вырасти из рядового маркетолога в руководителя службы или просто сменить вид деятельности и заняться маркетингом - этот курс для Вас! Курс ориентирован на широкую аудиторию, заинтересованную в изучении статистических экспериментов, A / B-тестирования и анализа данных. Студенты курса должны обладать базовыми компьютерными навыками и математическим образованием на уровне бакалавриата. A / B тестирование является популярным способом тестирования гипотез в маркетинге и набирает обороты в области науки о данных. В данном курсе мы покажем, что такое A / B-тестирование и как Вы можете использовать A / B-тестирование в науке о данных. Наш курс поможет вам - Строить гипотезы h0 и h1 для анализа данных - Определять соответствующий уровень статистической значимости для различных бизнес-целей - Видеть разницу между частотным и байесовским подходами - Проверять гипотезы и интерпретировать результаты. В заключение курса Вам предстоит проанализировать данные А/Б тестирования интернет-магазина. После прохождения курса Вы сможете: - провести регрессионный анализ и создать прогноз продаж на сайте, - использовать ансамблевые методы для улучшения качества прогнозной модели, - проверить статистику на наличие сезонности и обосновать маркетинговые решения, опираясь на анализ данных.

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Teaches the basics of statistical experiments and A/B testing, making it suitable for beginners

Covers advanced topics like seasonality and regression analysis, appealing to experienced learners

Taught by experts in marketing and data science, ensuring high-quality content

Focuses on practical applications, preparing learners for real-world scenarios

Provides a comprehensive understanding of statistical analysis, valuable for various industries

Requires prior knowledge in computer skills and mathematics, potentially limiting accessibility for some learners

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Learners who complete Статистика для обработки экспериментов и А/B-тестирования will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians apply statistical methods to solve problems and draw conclusions from data. This course provides a comprehensive foundation in statistical methods, including hypothesis testing, A/B testing, and data analysis techniques, which are essential skills for Statisticians. The course also covers regression analysis and forecasting, enabling Statisticians to build predictive models, quantify uncertainties, and provide insights based on data analysis. These skills are highly sought after in various industries, including healthcare, finance, and research.

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Marketing Analyst

Marketing Analysts use data to understand customer behavior and optimize marketing campaigns. This course provides a comprehensive foundation in statistical methods specifically tailored for marketing professionals. It covers hypothesis testing, A/B testing, and data analysis techniques, enabling Marketing Analysts to draw meaningful conclusions from data and make informed decisions. Additionally, the course's focus on building statistical models and forecasting helps Marketing Analysts predict future trends and forecast demand, making them invaluable assets in driving marketing strategies.

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Data Scientist

Data Scientists employ statistical methods to extract meaningful information from data. This course introduces essential statistical concepts, including hypothesis testing and interpretation, which are foundational skills for Data Scientists. Learning to conduct A/B testing and analyze data from experiments empowers Data Scientists to evaluate the effectiveness of marketing campaigns and optimize strategies. This course also covers regression analysis and forecasting, enabling Data Scientists to make predictions about future events. These skills are essential for building predictive models, which are used to guide decision-making and drive strategic initiatives.

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Quantitative Researcher

Quantitative Researchers use statistical methods to investigate social and economic issues. This course provides Quantitative Researchers with the statistical knowledge necessary to design and conduct research studies, analyze data, and draw meaningful conclusions. By understanding hypothesis testing, A/B testing, and data analysis techniques, Quantitative Researchers can contribute to evidence-based policy-making and decision-making. The course's focus on regression analysis and forecasting enables Quantitative Researchers to model complex relationships, predict future trends, and quantify uncertainties, making their research more impactful and reliable.

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Data Analyst

Data Analysts clean, process, and analyze data to extract meaningful insights for organizations. This course provides a solid foundation in statistical methods, including hypothesis testing, A/B testing, and data analysis techniques, which are essential skills for Data Analysts. The course's emphasis on regression analysis and forecasting enables Data Analysts to build predictive models and forecast future trends. These skills are critical in identifying patterns, predicting outcomes, and supporting decision-making in data-driven organizations.

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Risk Analyst

Risk Analysts use statistical methods to assess and manage risk. This course equips Risk Analysts with the statistical knowledge necessary to understand the principles of risk management, quantify risks, and make informed decisions. By learning hypothesis testing, A/B testing, and data analysis techniques, Risk Analysts can develop risk models, evaluate risk scenarios, and propose mitigation strategies to minimize financial losses and protect organizations from potential threats.

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Quantitative Trader

Quantitative Traders use statistical methods to develop and execute trading strategies. This course provides Quantitative Traders with the statistical knowledge necessary to understand financial markets, analyze trading data, and build predictive models for investment decisions. By understanding hypothesis testing, A/B testing, and data analysis techniques, Quantitative Traders can develop trading algorithms, optimize trading strategies, and make informed decisions about risk management and portfolio performance.

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Business Analyst

Business Analysts use data to identify business problems and develop solutions. This course equips Business Analysts with the statistical skills necessary to analyze business data effectively. By understanding hypothesis testing, A/B testing, and data analysis techniques, Business Analysts can make data-driven recommendations and drive business decisions that improve performance. The course also covers regression analysis and forecasting, enabling Business Analysts to predict future trends and forecast business outcomes. This knowledge empowers them to quantify the impact of business decisions and justify recommendations with supporting evidence.

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Financial Analyst

Financial Analysts use statistical methods to analyze financial data and make investment recommendations. This course provides Financial Analysts with the statistical knowledge necessary to understand financial markets, analyze investment opportunities, and make informed decisions about portfolio management. By understanding hypothesis testing, A/B testing, and data analysis techniques, Financial Analysts can develop financial models, assess investment risks and returns, and make recommendations for optimizing investment strategies and achieving financial goals.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical methods to optimize business operations. This course provides Operations Research Analysts with the statistical knowledge necessary to analyze business data, build models, and make recommendations for improving efficiency and effectiveness. By understanding hypothesis testing, A/B testing, and data analysis techniques, Operations Research Analysts can identify inefficiencies, optimize resource allocation, and develop data-driven solutions to improve business outcomes.

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Marketing Manager

Marketing Managers oversee the development and execution of marketing campaigns. This course provides Marketing Managers with the statistical knowledge necessary to evaluate the effectiveness of marketing strategies and optimize campaigns. By understanding hypothesis testing, A/B testing, and data analysis techniques, Marketing Managers can make informed decisions based on data and improve the impact of their marketing efforts. The course's focus on regression analysis and forecasting enables Marketing Managers to predict future trends and forecast demand, helping them plan and allocate resources effectively.

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Actuary

Actuaries use statistical methods to assess and manage financial risk. This course provides Actuaries with the statistical knowledge necessary to understand actuarial science principles, analyze data, and make informed decisions about risk and financial planning. By understanding hypothesis testing, A/B testing, and data analysis techniques, Actuaries can develop actuarial models, assess financial risks, and provide recommendations for mitigating financial risks and ensuring the financial security of individuals and organizations.

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Product Manager

Product Managers are responsible for developing and managing products that meet customer needs. This course equips Product Managers with the statistical knowledge necessary to understand user behavior and make data-driven product decisions. By learning hypothesis testing, A/B testing, and data analysis techniques, Product Managers can gather insights, test product features, and optimize the user experience. The course also covers regression analysis and forecasting, enabling Product Managers to predict future demand and plan product roadmaps based on data-driven evidence.

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Machine Learning Engineer

Machine Learning Engineers design and implement machine learning models. This course may be helpful for Machine Learning Engineers who want to gain a deeper understanding of the statistical underpinnings of machine learning. By learning hypothesis testing, A/B testing, and data analysis techniques, Machine Learning Engineers can build more robust and effective machine learning models.

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Data Engineer

Data Engineers design and manage data pipelines. This course may be helpful for Data Engineers who want to gain a deeper understanding of the statistical principles behind data analysis. By learning hypothesis testing, A/B testing, and data analysis techniques, Data Engineers can build more efficient and reliable data pipelines that support data-driven decision-making.

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Статистика для обработки экспериментов и А/B-тестирования

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