Algebra level symbolic math

  • A cartoon for use by teachers of night statistics classes. The cartoon is the work of Theresa McCracken and appears as #7178 on McHumor.com Free for non-profit use in statistics course such as in lectures and course websites.
    1
    Average: 1 (1 vote)
  • This applet builds confidence intervals for the percentage of orange candies in box with two colors of candies. A smaller box visualizes the sample, and a graph keeps track of the location of the confidence interval. Students can take one sample (producing one CI) repeatedly, or take 100 random samples at once. The population percentage is hidden from view unless the student asks to see it, in which case it is displayed on the graph of confidence intervals. This allows the students to see whether each interval "hits" or "misses". Several parameters can be varied: sample size, confidence level and number of samples. A set of questions alongside the applet guides students.

    0
    No votes yet
  • July 13, 2010 T&L webinar presented by Webster West (Texas A&M University) and hosted by Jackie Miller(The Ohio State University). In introductory statistics courses, web-based applets are often used to visually conduct large simulation studies illustrating statistical concepts. However, it is difficult to determine what (if anything) students learn from repeatedly pressing a button when using applets. More advanced options such as writing/running computer code are typically considered to be much too advanced for most introductory courses. The web-based software package, StatCrunch, now offers simulation capabilities that strike a middle ground between these two extremes. The instructor/student needs only to perform a small number of steps using the menu driven interface with each step being key to understanding the underlying data structure. This talk will cover the steps required to study concepts such as the central limit theorem, confidence intervals, hypothesis testing and regression using StatCrunch.
    0
    No votes yet
  • DataFerrett is a unique data analysis and extraction tool -- with recoding capabilities -- to customize federal, state, and local data to suit your requirements. Using DataFerrett, you can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands. The DataFerrett helps you locate and retrieve the data you need across the Internet to your desktop or system, regardless of where the data resides. You can then develop and customize tables. Selecting your results in your table you can create a chart or graph for a visual presentation into an html page. Save your data in the databasket and save your table for continued reuse. The DataFerrett is a Beta testing version that will incorporate the latest bug fixes, enhancements, and new functionality that will be rolled into the DataFerrett after testing has been completed.

    0
    No votes yet
  • This issue contains an article that provides an example of a paired samples test related to flying and gliding. It also includes an article about understanding confounding from lurking variables using graphs. Other articles include: a short description about what the t-tests actually tests, an interview with David Moore about why 30 is the "magic" number, a discussion about whether or not outliers should be deleted from a data set, a discussion of observational studies, and a simulation piece about random numbers from non-random arithmetic.
    0
    No votes yet
  • This issue contains an interview with Sallie Keller-McNulty and an article about which came first -- the chicken or the egg. Other articles include a discussion related to an AP Statistics example of seeing the trees for the forest (this focuses on understanding variability between groups and within groups), a discussion of how high r can go, a simulation piece focused on shrinking students, poisoned children, and bootsraps, and an example of a permutation test of the Challenger O-Ring data.
    0
    No votes yet
  • Every time man makes a new experiment he always learns more. He cannot learn less. is a quote of American inventor and author Richard Buckminster Fuller (1895-1983). The quote appears in his 1963 book "Operating Manual for Spaceship Earth".
    0
    No votes yet
  • A joke that might be used in discussing correlation - especially in health studies. The joke is adapted from a joke told by comedic magician Omar Covarrubias. The revised joke was written by Larry Lesser, University of Texas at El Paso, for use in the statistics classroom.
    0
    No votes yet
  • ...the most misleading assumptions are the ones you don't even know you're making is a quote by English author Douglas Noel Adams (1952-2001) that can be used in teaching the importance of understanding the assumptions being made that underlie statistical inference. The quote is from the 1990 book "Last Chance to See" that was co-written with Mark Carwardine. It is part of a passage that Adams wrote about his experience watching a silverback gorilla in Zaire and trying to imagine what the animal was thinking about him.
    0
    No votes yet
  • January 11, 2011 T&L webinar presented by Rakhee Patel(University of California - Los Angeles, UCLA) and hosted by Jackie Miller (The Ohio State University). Since formal hypothesis testing and inference methods can be a challenging topic for students to tackle, introducing informal inference early in a course is a useful way of helping students understand the concept of a null distribution and how to make decisions about whether to reject it. We will present two computer labs, both using Fathom, that illustrate these concepts using permutation in a setting where students will be answering interesting investigative questions with real data.
    0
    No votes yet

Pages