In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Trustworthy Science: Improving Statistical Reporting

Advance Organizer

We live in an era of unprecedented technology and science. Anyone alive during the space race and scientific advances of the 1960s and 1970s imagined a 21st century where we were living on the moon or in floating cloud cities on Earth, talking with robots, and living lengthy, healthy and happy lives, largely without problems or worry.1 Instead, we live in a 21st century world where people question whether vaccination of children is good, whether humans have impacted the environment, and whether evolution is a “belief” or a well-supported theory.

Trust of science is low among the general population and is decreasing precipitously in some segments (Gauchat, 2012). This is ironic given that there are more cell phones (brought ...

  • Loading...
locked icon

Sign in to access this content

Get a 30 day FREE TRIAL

  • Watch videos from a variety of sources bringing classroom topics to life
  • Read modern, diverse business cases
  • Explore hundreds of books and reference titles