Statistics for Researchers Training Course
Node ID: 13405
Duration
35 hours
Requirements
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: www.nobleprog.co.uk/training/statistics-level-1
Public Course Dates
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And we will organize the training at a location and date to suit you.
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| Date | Venue | Price | ||
|---|---|---|---|---|
| 2012-06-18 09:30 | Bristol, Temple Gate | From 1960 to 3980 GBP Check! | ||
| 2012-06-18 09:30 | London, Westbourne Grove | From 1960 to 3980 GBP Check! | ||
| 2012-06-25 09:30 | London, Westbourne Grove | From 1960 to 3980 GBP Check! | ||
| 2012-07-16 09:30 | Bristol, Temple Gate | From 1960 to 3980 GBP Check! | ||
| 2012-07-17 09:30 | Manchester | From 1960 to 3980 GBP Check! | ||
| 2012-07-30 09:30 | Bristol, Temple Gate | From 1764 to 3582 GBP Check! | ||
| 2012-08-06 09:30 | London, Westbourne Grove | From 1764 to 3582 GBP Check! | ||
| 2012-08-28 09:30 | Manchester | From 1764 to 3582 GBP Check! | ||
| 2012-09-17 09:30 | London, Westbourne Grove | From 1764 to 3582 GBP Check! | ||
| 2012-10-01 09:30 | Manchester | From 1764 to 3582 GBP Check! |
Overview
The course aims to give researchers to understand principles of statistical design and analysis and their relevance to research in a range of scientific disciplines.
It covers some probability and statistical methods, mainly through examples. Training contain around 30% of lectures, 70% of guided quizzes and labs.
In case of closed course we can tailor the examples and materials to a specific branch (like psychology tests, public sector, biology, genetics, etc...)
In case of public courses mixed examples are used.
Though various software is used during this course (Microsoft Excel to SPSS, Statgraphs, etc...) its main focus is on understanding principles and processes guding research, reasoning and conclusion.
This course can be delivered as a blended course i.e. with homework and assignments.
Course Outline
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
- Introduction
- Confidence Interval for the Mean
- t distribution
- Confidence Interval Simulation
- Confidence Interval for the Difference Between Means
- Confidence Interval for Pearson's Correlation
- Confidence Interval for a Proportion
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
Signficance Testing and Confidence Intervals
Misconceptions
Exercises
Testing Means
Single Mean
t Distribution Demo
Difference between Two Means (Independent Groups)
Robustnes 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
Power Demo 1
Power Demo 2
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
