Tuesday, Apr 19 from 12 to 1pm

Introduction to SPSS Part I

Dataset and Data Dictionary

Entering data manually

Importing data from Excel

Sorting and quick data inspection

Tuesday, Apr 26 from 12 to 1pm

Introduction to SPSS Part II

Recode

Compute

If conditional

Split File and Select Cases

Tuesday, May 03 from 12 to 1pm

Introduction to SPSS Part III

Crosstab

Means

Graphs

Explore

Tuesday, May 10 from 12 to 1pm

Introduction to SPSS Syntax

We will show you how the SPSS syntax works. This is about reproducibility, not coding/programing. The idea is that you have enough understanding of SPSS syntax so that you can use it if you want, but most importantly, keep a record of what you did.

Tuesday, May 17 from 12 to 1pm

SPSS Means and Proportions I

We will show how to compare means and proportions in SPSS. With this workshop we will enter Statistical Inference territory, and part of the workshop will be an overview of the scientific method, how statistics fits into it, and what p-values means.

We plan to cover:

t-tests for independent samples

Chi-square tests for contingence tables

Tuesday, May 24 from 12 to 1pm

SPSS Means and Proportions II

In this workshop we plan to finish covering location tests. We hope to cover:

Paired Sample t-test

Simple ANOVA (Analysis of Variance)

Non-parametric Mann-Whitney U test

Non-parametric Kruskal-Wallis H Testl

Non-parametric Wilcoxon Test

Non-parametric Friedman Test

Tuesday, May 31 from 12 to 1pm

SPSS Linear Regression I

We will cover linear regression in general, including:

Categorical and Continuous Variables

Variable Selection

Confounders

Predictive and Exploratory models

Coefficients and Interpretation

Tuesday, Jun 07 from 12 to 1pm

SPSS Logistic Regression

We will cover Logistic Regression, including:

Definition of binary outcomes, Probability, Odds and Risk

Logistic Regression basics and interpretation.

Tuesday, Jun 14 from 12 to 1pm

SPSS Mixed Models I

The workshop will cover:

Longitudinal Data;

Basics of fixed and random effects;

Restructuring Data in SPSS;

Within and Between Subject Variables;

Within subjet correlation;

Interpretation of Results.

Tuesday, Jun 21 from 12 to 1pm

SPSS Linear Regression II

We will expand on what we learned in the first workshop, including:

Interactions

Model Diagnostics (Influence, outliers)

Estimated Marginal Means

Tuesday, Jun 28 from 12 to 1pm

SPSS Mixed Models II

In this workshop we will dive a little deeper into Mixed Models and get some ideas of the different ways we can specify random effect and covariance structure for residuals.

Wednesday, Apr 20 from 12 to 1pm

R and RStudio - Overview

Software installation

What is R and RStudio

RStudio tour

Introduction to Script and Markcown

Wednesday, Apr 27 from 12 to 1pm

Introduction to R part I

Reaing data into R

Dataframes, lists, variables

How to work with dataframes in general

Missing values in R

Wednesday, May 04 from 12 to 1pm

Introduction to R part II

Some basic functions in R

Describing the data

Means, Standard Deviations

Tables

R Help

Wednesday, May 11 from 12 to 1pm

Introduction to package dplyr

dplyr is a R package quite useful for ‘data wrangling’. We will cover the primary functions:

mutate (creating new variables)

select (select columns)

filter (select rows)

arrange (sort)

summarise (summary stats)

“%>%” (forward pipe operator, from magrittr pacakge)

Wednesday, May 18 from 12 to 1pm

Introduction to package ggplot2

ggplot2 is a package for data visualization.

We will go over some basic graphs using ggplot2.

Scatterplot + smoothing line

Boxplot

Barchart

Line plot

Wednesday, May 25 from 12 to 1pm

Statistical Inference and Basic Stats I

Statistical Inference - Scientific Method, Sampling, Hypothesis Testing, p-values and Confidence Intervals.

Test of Means

Wednesday, Jun 01 from 12 to 1pm

R Basic Stats II

Non-parametric tests

Chi-square and Fisher's tests

Correlation tests

Wednesday, Jun 08 from 12 to 1pm

Linear Regression I

Simple and Multiple Linear Regression

Residuals adn Predicted Values

Influential Points and Outliers

Normality and Linearity

Interactions

Estimated Marginal Means

Wednesday, Jun 15 from 12 to 1pm

Linear Regression II

Same as above. The content will be convered in two workshops.

Wednesday, Jun 22 from 12 to 1pm

Logistic and Poisson Regression

Binary and Count data

Crosstable, Odds Ratio and Relative Risk

Probability and Odds Scale

Logistic Model

Poissson Model

Overdispersion

Estimated Marginal Means

Wednesday, Jun 29 from 12 to 1pm

Mixed Models

Longitudianl and Clustered data

Random Effects

Models for Covariance of Residuals

Non-normal data longitudinal data, Mixed Lotisitc Regerssion and GEE