While a gaming PC might cost more than an equivalent game console (a lot more, if you want enough power to run new games at the highest visual fidelity), you can save a lot of money on the games themselves if you're mindful. And most PC gamers do, according to a new consumer survey. The data says that only about a third of players on the PC will buy a game at its full, initial retail price (stretching into $70 USD for AAA games at this point) while the rest will wait for a sale or a bundle. The data comes from a consumer survey performed by secondary market Ultra and Atomik Research. According to aggregate answers from 2,000 PC gamers, only 36 percent of them will buy a new game at full price, while 32 percent will wait for a sale or a bundle (like the Humble Bundle).

Statistics is a huge field and many disciplines such as biology, economics and psychology have made significant contributions to it. This link to journals published by the American Statistical Association and this link regarding the popular statistical software R demonstrate just how big a field it is. Statistics is not just point-and-click and its growing complexity makes simplifying it more difficult, not easier. Moreover, in his popular textbook Statistical Rethinking, Richard McElreath of the Max Planck Institute makes a very important observation: "...statisticians do not in general exactly agree on how to analyze anything but the simplest of problems. The fact that statistical inference uses mathematics does not imply that there is only one reasonable or useful way to conduct an analysis. Engineering uses math as well but there are many ways to build a bridge."

Quantitative research has been defined in various ways. Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to predict or explain a particular phenomenon. In marketing research, "quant" historically has meant consumer surveys. Analysis of consumer survey data has typically been limited to reporting numbers, perhaps broken down by age group, gender and a few other respondent groups of interest. The emphasis is mainly on the Who, What, When, Where, and How, though segmentation, conjoint, key driver and other analyses that delve into the Why are also occasionally conducted with consumer survey data.

Structural Equation Modeling (SEM) is an extremely broad and flexible framework for data analysis, perhaps better thought of as a family of related methods rather than as a single technique. Its origins can be traced back to Psychologist Charles Spearman at the turn of the 20th century and Geneticist Sewall Wright in the immediate aftermath of WWI. Many others have had a hand in its development, notably Karl Jöreskog and Peter Bentler. Covariance Structure Analysis and LISREL, the name of a program Jöreskog co-developed, are other terms occasionally used interchangeably with Structural Equation Modeling. What is its relevance to Marketing Research?

Structural Equation Modeling (SEM) is an extremely broad and flexible framework for data analysis, perhaps better thought of as a family of related methods rather than as a single technique. Its origins can be traced back to Psychologist Charles Spearman at the turn of the 20th century and Geneticist Sewall Wright in the immediate aftermath of WWI. Many others have had a hand in its development, notably Karl Jöreskog and Peter Bentler. Covariance Structure Analysis and LISREL, the name of a program Jöreskog co-developed, are other terms occasionally used interchangeably with Structural Equation Modeling. What is its relevance to Marketing Research?