Statistics for Researchers培训




35 小时 通常来说是5天,包括中间休息。


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






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。


Machine Translated


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


  • 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


  • 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


  • Introduction
  • Example Calculations
  • Factors Affecting Power
  • Exercises


  • 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


  • 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







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