This post is based on this getting started guide found on aws.

Go to the Elasticsearch Service in the AWS Console.

Create an Amazon ES domain by clicking on the left-most blue button.


Overview

This post provides summary statistics for pools homes sold in the last six months in Lancaster, CA and Palmdale, CA. Here is a summary of the observations from the data:

  • Mean price is $450K and median prices is $400K, with a few outliers.
  • The average homes have 4 bedrooms & 2+ baths
  • The average square footage is a little over 2,000 sqft
  • The median lot size is 8,000+ square feet
  • The median home was built in 1989
  • There is a strong relationship between square footage and price, but as homes get larger than 3K square feet other factors drive more…


Do you want to get more done and feel more relaxed? Keep reading.

Personal Mentoring and Advice: If you like the article and want to get personalized mentoring and advice, schedule an initial consultation by clicking here.

Overview

I’ve had plenty of busy periods in my life. Here are some of the most active periods I’ve experienced in the last fifteen years:

  • Working full-time while earning six college degrees.
  • Becoming a manager & father and commuting three hours a day.
  • Learning how to program and do real estate investing.
  • Building a patented Artificial Intelligence system for fun.
  • Earning multiple promotions & taking about 30 online classes.
  • Dual career couple working through a pandemic with…


Personal Mentoring and Advice: If you like the article and want to get personalized mentoring and advice, schedule an initial consultation by clicking here.

Introduction

Over the last six years, I’ve read a ton of data science books. The combination of books, classes, projects, and real-life working experience on projects was a powerful in my development as a data scientist. I want to share with a simple roadmap and the best books I found along my journey.

I leveraged books, personal projects, and real-life work experience to work as a data analyst, then data scientist, and finally, as a leader of…


Personal Mentoring and Advice: If you like the article and want to get personalized mentoring and advice, schedule an initial consultation by clicking here.

Quick Introduction

I graduated during the last global recession. It was a real struggle, but I learned and hustled my way to a rewarding, and satisfying career in Data Science. I went from being rejected hundreds of times after graduation to working in the world’s most admired companies over the course of ten years.

I want to share my knowledge and experience with recent grads in today’s economy. Here is a summary

  • A lousy economy will hurt your…


Useful Books for This Topic:

This post presents the ordinary least squares assumptions. The assumptions are critical in understanding when OLS will and will not give useful results. The objective of the following post is to define the assumptions of ordinary least squares. Another post will address methods to identify violations of these assumptions and provide potential solutions to dealing with violations of OLS assumptions.

ASSUMPTION #1: The conditional distribution of a given error term given a level of an independent variable x has a mean of zero.

This assumption states that…


Overview

An impulse response function describes who shocks to a system of equations that affects those equations over time. In economics, one might be interested in understanding how a sudden and unexpected change in one variable impact another variable over time. Following the data and SVAR calculations in the previous post, this entry will graph impulse response functions and generate tables to illustrate how a one-unit change in the log difference in income and investment impacts consumption.

Useful Books on Topic:

Generating Impulse Response Functions

Like in the previous post, calculations were made in…


Introduction

The price of a home can be affected by current interest rates, unemployment rates, and a host of other macroeconomic factors. Home prices are also subject to microeconomic externalities. These externalities can take the form of neighborhood characteristics such as quality of schools, crime, and even the proximity to garbage dumps. To quantify the impact of a building a garbage incinerator in North Andover, Massachusetts, had on home prices, Kiel and McClain estimated it impacts using a Difference-in-Difference Model. …


Introduction

In regression analysis, variables can be endogenous for several reasons, including omitted variable bias, measurement error, and simultaneity / reverse causation. One example from the previous post was that of unobserved ability in the determination of wages. Overestimation for the returns occurs when omitting unobserved ability in the analysis of education’s impact on wages.

Useful books for understanding material:

The Hausman Test

The Hausman Test for endogeneity can help us determine whether or not there is some form of omitted variable bias in this regression:

JJ Espinoza

Senior Data Scientist, Economist, Investor, and Technologist

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store