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Interpretation of Confidence Levels

  • The researcher armed with a confidence interval, but deprived of the false respectability of statistical significance, must work harder to convince himself and others of the importance of his findings. This can only be good. is a quote by British statistician Michael W. Oakes. The quote is found in his 1986 book "Statistical Inference: a Commentary for the Social and Behavioural Sciences" published by John Wiley & Sons.

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  • A joke to be used in teaching about the use of randomization in experiments or about the Pearson correlation coefficient. The idea for the joke came from Lawrence Mark Lesser of The University of Texas at El Paso in 2012.

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  • A cartoon to use when talking about confidence intervals. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • In this video (which lasts almost 20 minutes), statistics guru Hans Rosling debunks myths about the so-called "developing world."
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  • A cartoon to teach about the interpretation of confidence statements. The cartoon plays on the idea of what would happen if the same process was repeated over-and-over again. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

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  • Song about bootstrap resampling methods and their history. May be sung to the tune of Don McLean's 1971 song "American Pie." Lyrics by Giles Hooker (May, 2004). This song is part of the "Stanford Statistics Songbook" found at www.bscb.cornell.edu/~hooker/StanfordStatisticsSongbook.pdf Free to use for non-commercial educational purposes. Contact author to use in publications or for commercial purposes. Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • A cartoon to teach about confidence intervals. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

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    Average: 5 (1 vote)
  • This group activity illustrates the concepts of size and power of a test through simulation. Students simulate binomial data by repeatedly rolling a ten-sided die, and they use their simulated data to estimate the size of a binomial test. They carry out further simulations to estimate the power of the test. After pooling their data with that of other groups, they construct a power curve. A theoretical power curve is also constructed, and the students discuss why there are differences between the expected and estimated curves. Key words: Power, size, hypothesis testing, binomial distribution
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  • This activity illustrates the convergence of long run relative frequency to the true probability. The psychic ability of a student from the class is studied using an applet. The student is asked to repeatedly guess the outcome of a virtual coin toss. The instructor enters the student's guesses and the applet plots the percentage of correct answers versus the number of attempts. With the applet, many guesses can be entered very quickly. If the student is truly a psychic, the percentage correct will converge to a value above 0.5.
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  • A cartoon to teach about the distributional assumptions in linear models. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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