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Statistical Consulting Center Courses

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Fundamentals of Statistics

Course Program:

Module 1: Study Design, Statistical Significance

  • Intro, Study Design
  • Measures of Central Location and Variability
  • Distance
  • Data Format
  • Variables
  • Graphs
  • Null Hypothesis
  • Resampling
  • Normal Distribution
  • Significance

Module 2: Categorical Data, Contingency Tables

  • Categorical Data
  • Graphical Exploration
  • Indexing
  • Simple Probability
  • Distributions
  • Normal Distribution again
  • 2-Way (Contingency) Tables
  • Conditional Probability

Module 3: More Probability and Random Sampling

  • Bayes Rule

  • Independence

  • Surveys

  • Random Sampling

Module 4: Confidence Intervals

  • Point Estimates

  • Confidence Intervals

  • Formula Counterparts

  • Standard Error

  • Beyond Random Sampling

Module
5: Confidence Intervals for Proportions; 2-Sample Comparisons

  • CI for a proportion

  • The language of hypothesis testing

  • A-B tests

  • Bandit Algorithms (briefly)

Module
6: Correlation and Simple (1-variable) Regression

  • Correlation coefficient

  • Significance testing for correlation

  • Fitting a regression line by hand

  • Least squares fit

  • Using the regression equation

Module
7: Multiple Regression

  • Multiple predictor variables

  • Assessing the regression model

  • Goodness-of-fit (R-squared)

  • Interpreting the coefficients

  • RMSE (root mean squared error)

Registration

Please read the Booking Terms and Conditions before you book your course. By making a booking you will be deemed to have read, understood and accepted the booking terms and conditions.
Book Now

Introduction to Research Methods

Description

This course will provide an opportunity for participants to establish or advance their understanding of research through critical exploration of research language, ethics, and approaches. The course introduces the language of research, ethical principles and challenges, and the elements of the research process within quantitative, qualitative, and mixed methods approaches. Participants will use these theoretical underpinnings to begin to critically review literature relevant to their field or interests and determine how research findings are useful in informing their understanding of their environment (work, social, local, global).

Objectives

At the conclusion of the course, the participant will:

  • Understand research terminology

  • Be aware of the ethical principles of research, ethical challenges

  • and approval processes

  • Describe quantitative, qualitative and mixed methods approaches to
    research

  • Identify the components of a literature review process

  • Critically analyze published research

Module 1: Introduction to Research

  • Lesson 1: What is Research?

  • Lesson 2: Research Concepts

  • Lesson 3: Research Ethics and Integrity

Module 2: Quantitative Research Methods

  • Lesson 4: The Scientific Method

  • Lesson 5: Design of Quantitative Surveys

  • Lesson 6: Quantitative Research Methods–Wrap-Up

Module 3: Qualitative Research

  • Lesson 7: Introduction to Qualitative Research and Research
    Approaches

  • Lesson 8: Qualitative Research Methods–The Toolkit

  • Lesson 9: Data Analysis and Theory in Qualitative Research Articles

Module 4: Mixed-Methods Design

  • Lesson 10: Introduction to Mixed Methods Research

  • Lesson 11: Design of Mixed Methods Research

  • Lesson 12: Evaluation of Mixed Methods Research

EVIEWS

EViews offers academic researchers, corporations, government agencies, and students access to powerful statistical, forecasting, and modeling tools through an innovative, easy-to-use object-oriented interface. Areas where EViews can be useful include scientific data analysis and evaluation, financial analysis, macroeconomic forecasting, simulation, sales forecasting, and cost analysis.
EViews blends the best of modern software technology with cutting edge features. The result is a state-of-the art program that offers unprecedented power within a flexible, easy-to-use interface. Explore the world of EViews and discover why it is the worldwide leader in Windows-based econometric software and the choice of those who demand the very best!

Module 1: EViews Fundamentals

Introduces you to the basics of using EViews. In addition to a discussion of basic Windows operations, we explain how to use EViews to manage your data.

Module 2: Basic Data Analysis

Describes the use of EViews to perform basic analysis of data and to draw graphs and create tables describing your data.

Module 3: Basic Single Equation Analysis

Discusses standard regression analysis: ordinary least squares, weighted least squares, two-stage least squares, nonlinear least squares, time series analysis, specification testing and forecasting.

Module 4: Advanced Single Equation Analysis

Autoregressive conditional heteroskedasticity (ARCH) models, discrete and limited dependent variable models, and user specified likelihood estimation.

Registration

Please read the Booking Terms and Conditions before you book your course. By making a booking you will be deemed to have read, understood and accepted the booking terms and conditions. Book Now