I wish I could remember where I copied and pasted this from, but alas, I cannot. Just the same, here's a great overview of what a data scientist would benefit from understanding.
At a minimum, a data scientist needs to be proficient with concepts such as probability, correlation, variables, distributions, regression, null hypothesis significance tests, confidence intervals, t-test, ANOVA, and chi-square. At an advanced stage, data scientists need concepts and algorithms such as logistic regression, support vector machines (SVMs) and Bayesian methods. Common statistical analysis tools such as Excel, R and SAS are very famous among data scientists.
In February of 2018, I was denied admission to a Ph.D. program in Linguistics. As I was navigating the application process, I simultaneously revisited a dormant interest in computer science. In March I enrolled in a certified Computer Science class via HarvardX, which I completed four months later. I am at the beginning of a new phase in my life-long learning process and look forward to that which the future will inevitably deliver.
Showing posts with label SAS. Show all posts
Showing posts with label SAS. Show all posts
Wednesday, July 4, 2018
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SQL
I've hit a wall in my SQL studies via the Khan Academy, and as such, I am engaging in additional studies prior to attempting to move for...

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I've hit a wall in my SQL studies via the Khan Academy, and as such, I am engaging in additional studies prior to attempting to move for...
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I wish I could remember where I copied and pasted this from, but alas, I cannot. Just the same, here's a great overview of what a data s...