Probability statistics

Bài giảng Xác suất thống kê có kết cấu gồm 2 phần. Trong đó phần 1 gồm 5 chương trình bày về biến cố ngẫu nhiên và xác suất, biến ngẫu nhiên, một số quy luật phân phối sác xuất của biến ngẫu nhiên, biến ngẫu nhiên nhiều chiều, luật số lớn - các định lý giới hạn; Phần 2 gồm 3 chương giới thiệu về cơ sở lý thuyết mẫu, ước lượng tham số, kiểm định giả thuyết thống kê. Mời các bạn cùng tham khảo.

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Lectures "Applied statistics for business - Chapter 4: Introduction to probability" provides students with the knowledge: Experiments, counting rules and assigning probabilities, events and their probabilities, some basic relationships of probability, conditional probability, bayes’ theorem. Invite you to refer to the disclosures.

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Lectures "Applied statistics for business - Chapter 5: Discrete probability distributions" provides students with the knowledge: Random variables, developing discrete probability distributions, expected value and variance, expected value and variance financial portfolios,... Invite you to refer to the disclosures.

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Lecture Monte carlo simulations: Application to lattice models, part I - Basics. The main contents of this chapter include all of the following: Introduction, thermodynamics and statistical mechanics, phase transition, probability theory.

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Lecture "Probability & statistics - Chapter 1: Intruction" has contents: Statistics is the fact, statistics, branches of statistics, data sources, population and sample, types of variable types of variable,... Invite you to consult the content.

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Lecture "Probability & statistics - Chapter 2: Tables & charts" has contents: Frequency, relative frequency, cumulative table; pie chart; bar chart, column chart; histogram; line chart; radar chart; rcatter plot, bubble chart.

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Lecture "Probability & statistics - Chapter 3: Numerical summary" has contents: Data measurements, locations, variability measures, shape, arithmetic mean, compare the mean, mode, quartile, range, variance & standard deviation.... Invite you to consult the content.

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Lecture "Probability & statistics - Chapter 4: Basic probability" has contents: Probability, outcome – event complement event, intersection event, union event mutually exclusive, independent, collectively exhausive, partitions bernoulli formula total probability, bayes’ theorem.

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Lecture "Probability & statistics - Chapter 5: Discrete probability" has contents: Random variable, probability distribution, expected value, variance – standard deviation, bivariate probability, binomial distribution.

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After studying this chapter you will be able to: Introduction to statistics, methods for describing data, probability, discrete probability distributions, the normal probability distribution, confidence interval, hypothesis testing.

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Objective of the research: The research objective of the thesis is to establish some limit theorems regarding the forms of law of large numbers for sequences and arrays of measurable operators under different conditions.

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"Đề cương chi tiết học phần Xác suất thống kê (Probability and Statistics) bậc đại học" cung cấp các thông tin như thời gian, điều kiện tiên quyết, kiến thức, mô tả tóm tắt nội dung, các kỹ năng và yêu cầu mà sinh cần đạt được.

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Mời các bạn cùng tham khảo "Đề cương chi tiết học phần Xác suất thống kê (Probability and Statistics)" để nắm chi tiết thời gian, tóm tắt nội dung, thang điểm, các thang điểm để có phương pháp học tập chủ động và hiệu quả.

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The object (for students) in this course is: To learn how to interpret statistical summaries appearing in journals, newspaper reports, internet, television, etc; to learn about the concepts of probability and probabilistic reasoning; to understand variability and analyze sampling distribution; to learn how to interpret and analyze data arising in your own work (course work or research).

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A Bayesian approach with frequentist validity has been developed to support inferences derived from a BLevel A^ in vivo-in vitro correlation (IVIVC). Irrespective of whether the in vivo data reflect in vivo dissolution or absorption, the IVIVC is typically assessed using a linear regression model. Confidence intervals are generally used to describe the uncertainty around the model. While the confidence intervals can describe population-level variability, it does not address the individual-level variability.

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Lecture "Probability & statistics - Chapter 6: Continuous probability" has contents: Continuous random variable, density function, parameter, uniform distribution, normal distribution, cutoff point. Invite you to consult the content.

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Lecture "Probability & statistics - Chapter 7: Sampling" has contents: Sampling, sampling distribution, point estimate, acceptance interval, random sample, sampling distribution, acceptance interval.

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Lecture "Probability & statistics - Chapter 8: Estimation" has contents: Concept of estimate, point estimate, maximum likelihood estimate, interval estimate, for mean, for proportion, for variance. Invite you to consult the content.

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Lecture "Probability & statistics - Chapter 9: Hypothesis testing" has contents: Statistical hypothesis, error types, T-test for mean, Z-test for population, chi-sq test for variance. Invite you to consult the content.

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Lecture "Probability & statistics - Chapter 10: Two populations testing" has contents: Two independent population, T- test for Means, Z - test for Proportion. Invite you to consult the content.

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