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Statistics for Researchers

Training

In Manchester ()

Price on request

Description

  • Type

    Training

  • Class hours

    35h

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. Suitable for: A solid understanding of descriptive statistics and basic understanding or probability is required.

About this course

Solid understanding of descriptive statistics (mean, average, standard deviation, variance) and basic understanding of probability is required.

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Subjects

  • Interpreting
  • Decision Making
  • Testing
  • Statistics
  • Design
  • Simulation
  • Public
  • Confidence Training
  • Probability
  • Satistic

Course programme

Course review:

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

Statistics for Researchers

Price on request