This month we are featuring a 9-module software tutorial by Kim Love: An Introduction to Data Analysis using R.
It’s perfect for people who:
Tell me if you can relate to this:
You love your field of study, you enjoy asking the big questions and discovering answers. But, when it comes to data analysis and statistics you get a little bogged down. You might even feel a bit lost sometimes.
Because after all, you are supposed to be the expert. Right?
The thing is, statistics is a field unto itself. But as a researcher, you need to be adept with statistics even though you may only have very basic training in this field. In essence, you learned statistics — a new language — out of context. You had no real immersion experience to practice this language. You had few opportunities to apply the strange new terms and concepts as you learned them.
At the Analysis Factor, we understand the pain of learning and doing statistics. We have been in the trenches with hundreds of researchers like you across many fields of study. Everyone is struggling to grow their statistical, data analysis, and software skills.
In Statistically Speaking we support and guide you as you learn — every step of the way. We know where to start, where to go next, and next, and next.
We know that your field and research question(s) determine the type of data and complexity of statistical analyses you will choose. And we know that everyone shows up in a different place, and needs different things to help them get where they need to go.
So we have created a treasure trove of resources on hundreds of topics — from data cleaning and research design to logistic regression and structural equation modeling.
And to keep it all about you, we have created a customizable learning platform, one where you make a plan for your own unique journey. We have crafted a series of comprehensive Maps, curated guides on essential topics at each Stage of mastery, offering you a structured pathway through the maze of statistical knowledge.
You create the plan you need, and choose the maps you need to do your research.
At The Analysis Factor, we classify the statistical content and skills into 4 Stages to help you decide where to begin your learning journey. In Statistically Speaking, the Maps are categorized into these Stages.
Here are just a few examples:
Preparing Data: Understanding the fundamental steps in data preparation, from cleaning and transforming to structuring datasets for analysis.
Bivariate Statistics: Grasping the basics of relationships between two variables, laying the groundwork for more complex analyses.
Graphing: Learning visualization techniques to represent data and derive meaningful insights.
Introduction to Regression: Unraveling the fundamentals of regression analysis, a cornerstone of statistical modeling.
Interpreting Results: Developing the skill to interpret statistical results and draw valid conclusions from analyses.
Count Models: Exploring specialized models for count data analysis, understanding their application and nuances.
Logistic Regression: Diving into binary outcome analysis, understanding probabilities, and logistic models.
Factor Analysis: Delving into multivariate analysis, understanding latent variables and their relationships.
GLMM: Embracing the complexity of generalized linear mixed models, integrating fixed and random effects.
SEM: Venturing into structural equation modeling, exploring complex relationships among variables.
Survival Analysis: Understanding time-to-event data, its application in various fields, and survival modeling techniques.
By mapping out the key content and skills you want to learn at each Stage, you’ll gain a clearer understanding of the vast statistical landscape and feel empowered to take on the learning journey ahead.
So, what are you waiting for? Members, head on over to explore the Maps in Statistically Speaking.
And if you are not yet a member, you can sign-up for our waitlist to join Statistically Speaking. We would love to meet you, learn about your research, and help you get started on your statistical learning adventure.
So, you want to get started with Stata?
Good choice!
At The Analysis Factor we recommend first becoming proficient in one statistical software. Then once you’ve progressed up to learning Stage 3 skills, adding a second statistical software. Whether it’s your first, second, or 5th statistical software, Stata has a lot that makes it worth learning.
When I first started using Stata, I remember being confused by the variety of menus and windows, the strange syntax of the code, the way it handled datasets… and what the heck is a do file? (more…)
Many data sets are challenging and time consuming to work with because the data are seldom in an optimal format.
You may have heard that using SPSS syntax is more efficient, gives you more control, and ultimately saves you time and frustration. It’s all true.
….And yet you probably use SPSS because you don’t want to code. You like the menus.
I get it.
I like the menus, too, and I use them all the time.
But I use syntax just as often.
At some point, if you want to do serious data analysis, you have to start using syntax. (more…)
In this 8-part tutorial, you will learn how to get started using Stata for data preparation, analysis, and graphing. This tutorial will give you the skills to start using Stata on your own. You will need a license to Stata and to have it installed before you begin.