2016-08-16

Transitioning to Project Management

As I transition back to project management work, as well as pick up more business analysis skill, I have found it useful to work through a few Pluralsight videos. First, I was quite surprised how much I got from learning more about MS Project. It s much more that just Gantt charting! As for project management, some elements are native to anyone that plans, like a work breakdown structure or the timeline, but there are very important aspects of issue control and communication that need to be part of one's PM toolkit.
2016-06-24

Ten Simple Rules for Effective Statistical Practice

A interesting article by six statisticians, Ten Simple Rules for Effective Statistical Practice, and their aim:
To this point, Meng notes "sound statistical practices require a bit of science, engineering, and arts, and hence some general guidelines for helping practitioners to develop statistical insights and acumen are in order. No rules, simple or not, can be 100% applicable or foolproof, but that's the very essence that I find this is a useful exercise. It reminds practitioners that good statistical practices require far more than running software or an algorithm."
The 10 rules are:

  1. Statistical Methods Should Enable Data to Answer Scientific Questions
  2. Signals Always Come with Noise
  3. Plan Ahead, Really Ahead
  4. Worry about Data Quality
  5. Statistical Analysis Is More Than a Set of Computations
  6. Keep it Simple
  7. Provide Assessments of Variability
  8. Check Your Assumptions
  9. When Possible, Replicate!
  10. Make Your Analysis Reproducible
2016-03-28

Data Analytics Workouts: Recent Posts using R

Below are some recent posts regarding my work learning R, where I took prior work I had done in Excel, country correlations on human welfare, or F#, solving Project Euler problems, and re-executed them, and to some degree improved upon them.

Plotting Text Frequency and Distribution using R for Spinoza's A Theological-Political Treatise [Part I]

Inequality Kills: Correlation, with Graph and Least Square, of Gini Coefficient (Inequality) and Infant Death

Chi-Square in R on by State Politics (Red/Blue) and Income (Higher/Lower)

Logistic Regression in R on Politics and Income

Multiple Regression with R, on IQ for Gini and Linguistic Diversity

Linear Regression with R, on IQ for Gini and Linguistic Diversity

Mean Median, and Mode with R, using Country-level IQ Estimates

Correlations within with Hofstede's Cultural Values, Diversity, GINI, and IQ

ANOVA with Hofstede's Cultural Values and Economic Outcomes

Text Parser and Word Frequency using R

Project Euler: F# to R
2016-03-28

Data Analytics Workouts: Recent Posts using Python

I have been exploring Python and R for manipulating data. My long terms goals for this exercise, that I document on the blog, are to develop skills in the aforementioned languages, as well as extend my abilities with F# and explore other technologies like NoSQL Db's. Things like Hadoop and Spark are likely much farther down the road, if at all.

Exercises: OESMN (Obtaining, Scrubbing, Exploring, Modeling, iNterpreting)

OESMN (Obtaining, Scrubbing, Exploring, Modeling, iNterpreting): Getting Data

Computational Statistics in Python: Exercises

Promising Power: functools and itertools of Python

Iterators, Generators, and Decorators in Python

Recursion in Python

Functions are first class objects: Higher Order Functions
2016-03-15

Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences)

Text Analysis with R for Students of Literature (Quantitative Methods in the Humanities and Social Sciences)Text Analysis with R for Students of Literature by Matthew L. Jockers
My rating: 5 of 5 stars

I've just started reading this, but so far it's very promising...

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