TAILIEUCHUNG - Lecture Probability & statistics: Chapter 8 - Bùi Dương Hải

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. | Lecture Probability & statistics: Chapter 8 - Bùi Dương Hải Lecture 8. ESTIMATION [1] Chapter 8, Chapter 11 Concept of Estimate Point Estimate Maximum Likelihood Estimate Interval Estimate For Mean For Proportion For Variance (pp. 484 – 488) PROBABILITY & STATISTICS – Bui Duong Hai – NEU – 1 . Concept of Estimate Estimation is determining the approximate value of a unknown parameter on given data. Two types of estimate: Point estimate: single value Interval estimate: an interval that parameter falls into it with a determined probability level Ex. “The average height of VN’s male is 163 cm” “The average height of VN’s male is from 160 to 165 cm” PROBABILITY & STATISTICS – Bui Duong Hai – NEU – 2 . Point Estimate Point estimate of parameter is denoted by Estimator: a statistic calculated on random sample, an approximation to unknown parameter. Estimator is a random variable Estimate: specific value calculated on observed sample. Estimate is number. ∑ Ex. Formula ̅ = is an estimator Value ̅ = = 5 is an estimate PROBABILITY & STATISTICS – Bui Duong Hai – NEU – 3 Point Estimate Population parameters , , are unknown Estimate by statistics from sample Sample mean ̅ is point estimate for Sample variance is point estimate for Sample proportion ̅ is point estimate for PROBABILITY & STATISTICS – Bui Duong Hai – NEU – 4 Properties of Point Estimate Estimate for by Unbiased: is unbiased estimator of = Efficient: and are unbiased, is more efficient than : < If is smallest in every unbiased estimator: most efficient, best estimator BUE (Best Unbiased Estimator) PROBABILITY & STATISTICS – Bui Duong Hai – NEU – 5 Example . Population mean , sample ( , , , ) (a)

• Toán học
• Lecture Probability & statistics
• Probability & statistics
• Tính toán và thông kê
• Point estimate
• Maximum likelihood estimate
• Interval estimate
• Discrete probability
• Standard deviation
• Bivariate probability
• Basic probability
• Union event mutually exclusive
• Partitions bernoulli formula
• Continuous probability
• Continuous random variable
• Density function
• Lecture Business statistics
• Bài giảng Thống kê doanh nghiệp
• Business statistics
• Continuous probability distributions
• Uniform probability distribution
• Normal probability distribution
• Data sources
• Population and sample
• Variable types of variable
• Relative frequency
• Cumulative table
• Line chart
• Numerical summary
• Data measurements
• Compare the mean
• Sampling distribution
• Scceptance interval
• Hypothesis testing
• Statistical hypothesis
• Error types
• Two populations testing
• Two independent population
• T test for Means
• Discrete probability distributions
• Binomial probability distribution
• Random variables
• Basic statistics
• Statistics for business
• Describing data
• Probability concepts
• Joint probability
• Contingency table
• Probability distribution
• Uniform distribution
• Elementary Statistics
• Lecture note Elementary Statistics
• Thống kê căn bản
• Methods for describing data
• The normal probability distribution
• Statistical techniques
• Descriptive statistics
• Mutually exclusive events
• Addition lawfor mutually exclusive events
• Computing probability
• Business statistics in practice
• Sample spaces
• Elementary probability rules
• Compute conditional probabilities
• Discrete random variables
• Binomial distribution
• Continuous random variables
• Lecture Basic Statistics
• Bài giảng Thống kê cơ bản
• The normal distribution
• Percentile ranks
• The binomial distribution
• Inferential statistics
• Conditional probability
• Bayes’ theorem
• Sampling methods
• Central limit theorem
• Probability sampling