课程编码
statsres
课程时长
35 小时 通常来说是5天,包括中间休息。
要求
Solid understanding of descriptive statistics (mean, average, standard deviation, variance) and basic understanding of probability is required.
You may want to participate in preparation course: Statistics Level 1
课程概览
本课程旨在让研究人员了解统计设计和分析的原理及其与一系列科学学科研究的相关性。
它主要通过实例介绍了一些概率和统计方法。该培训包含约30%的讲座,70%的指导测验和实验。
在封闭课程的情况下,我们可以将示例和材料定制到特定的分支(如心理学测试,公共部门,生物学,遗传学等...)
在公共课程的情况下,使用混合的例子。
虽然在本课程中使用了各种软件(Microsoft Excel to SPSS,Statgraphics等),但其主要重点是理解指导研究,推理和结论的原则和过程。
本课程可以作为混合课程提供,即与家庭作业和作业。
Machine Translated
课程大纲
Scientific Method, Probability & Statistics
- Very short history of statistics
- Why can be "confident" about the conclusions
- Probability and decision making
Preparation for research (deciding "what" and "how")
- The big picture: research is a part of a process with inputs and outputs
- Gathering data
- Questioners and measurement
- What to measure
- Observational Studies
- Design of Experiments
- Analysis of Data and Graphical Methods
- Research Skills and Techniques
- Research Management
Describing Bivariate Data
- Introduction to Bivariate Data
- Values of the Pearson Correlation
- Guessing Correlations Simulation
- Properties of Pearson's r
- Computing Pearson's r
- Restriction of Range Demo
- Variance Sum Law II
- Exercises
Probability
- Introduction
- Basic Concepts
- Conditional Probability Demo
- Gamblers Fallacy Simulation
- Birthday Demonstration
- Binomial Distribution
- Binomial Demonstration
- Base Rates
- Bayes' Theorem Demonstration
- Monty Hall Problem Demonstration
- Exercises
Normal Distributions
- Introduction
- History
- Areas of Normal Distributions
- Varieties of Normal Distribution Demo
- Standard Normal
- Normal Approximation to the Binomial
- Normal Approximation Demo
- Exercises
Sampling Distributions
- Introduction
- Basic Demo
- Sample Size Demo
- Central Limit Theorem Demo
- Sampling Distribution of the Mean
- Sampling Distribution of Difference Between Means
- Sampling Distribution of Pearson's r
- Sampling Distribution of a Proportion
- Exercises
Estimation
- Introduction
- Degrees of Freedom
- Characteristics of Estimators
- Bias and Variability Simulation
- Confidence Intervals
- Exercises
Logic of Hypothesis Testing
- Introduction
- Significance Testing
- Type I and Type II Errors
- One- and Two-Tailed Tests
- Interpreting Significant Results
- Interpreting Non-Significant Results
- Steps in Hypothesis Testing
- Significance Testing and Confidence Intervals
- Misconceptions
- Exercises
Testing Means
- Single Mean
- t Distribution Demo
- Difference between Two Means (Independent Groups)
- Robustness Simulation
- All Pairwise Comparisons Among Means
- Specific Comparisons
- Difference between Two Means (Correlated Pairs)
- Correlated t Simulation
- Specific Comparisons (Correlated Observations)
- Pairwise Comparisons (Correlated Observations)
- Exercises
Power
- Introduction
- Example Calculations
- Factors Affecting Power
- Exercises
Prediction
- Introduction to Simple Linear Regression
- Linear Fit Demo
- Partitioning Sums of Squares
- Standard Error of the Estimate
- Prediction Line Demo
- Inferential Statistics for b and r
- Exercises
ANOVA
- Introduction
- ANOVA Designs
- One-Factor ANOVA (Between-Subjects)
- One-Way Demo
- Multi-Factor ANOVA (Between-Subjects)
- Unequal Sample Sizes
- Tests Supplementing ANOVA
- Within-Subjects ANOVA
- Power of Within-Subjects Designs Demo
- Exercises
Chi Square
- Chi Square Distribution
- One-Way Tables
- Testing Distributions Demo
- Contingency Tables
- 2 x 2 Table Simulation
- Exercises
Case Studies
Analysis of selected case studies