STAT 3010 – Intermediate Statistical Concepts and Methods

Description 

STAT 3010 is a second course in statistics. The JMP Software program will be used to analyze data. Students will learn how to display data in a graph using multiple variables and build statistical models. Analyses discussed include basics such as inference of a single sample up through more complex models such as multiple regression and indicator variables.

 

Prerequisite 

STAT 1010, STAT 1040, STAT 1050, STAT 2010, or equivalent from a Statistics Department.

 

Recent Instructors 

 

Textbooks 

Here is a list of possible textbooks:

  • STAT2: Modeling with Regression and ANOVA + Achieve, 2nd edition (2019); Cannon, Cobb, Hartlaub, Legler, Lock, Moore, Rossman, & Witmer. (Available via Immediate Access on Canvas)
  • Free Online access to OpenIntro Statistics, 4th edition (2022); Diez, Cetinkaya-Rundel, & Barr

 

Offerings 

Offered during Fall and Spring semesters and summer session each year.

 

Previous Course Number

301

 

Topics

General topics include:

  • Understand the difference between parameters versus statistics.
  • Analyze and interpret data from observational studies.
  • Understand how statistical models are used to represent relationships in data.
  • Extend and build on simple linear regression techniques discussed in your introductory statistics course. 
  • Use statistical methods to reach informed decisions about questions arising from real-world problems.
  • Model relationships between a numerical response and one or more numerical or categorical explanatory variables.
  • Recognize the conditions necessary for an appropriate statistical analysis, how to check if those conditions are met, and understand the consequences of violating those conditions.

 

Statistical analyses include:California Elementary Schools Scatterplot

  • Short review of Introductory Statistics
  • Simple linear regression
  • Inference for simple linear regression
  • Multiple regression first order models
  • Inference for multiple regression
  • Multiple regression with categorical variables
  • Multiple regression second order models
  • One-way ANOVA
  • Contingency tables and Chi-square tests
  • Logistic regression

 

 

Source:  WikiEducator