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  • This activity begins with an instructor demonstration followed by a student out-of-class assignment. Students will observe their instructor create a scatterplot and observe how the correlation coefficient changes when outlier points are added. Students are then given a follow up assignment, which guides them through the applet. In addition, the assignment provides insight about outliers and their effect on correlation. This activity will show exactly how outliers numerically change the correlation coefficient value and to what degree.
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  • This visualization activity combines student data collection with the use of an applet to enhance the understanding of the distributions of slope and intercept in simple linear regression models. The applet simulates a linear regression plot and the corresponding intercept and slope histograms. The program allows the user to change settings such as slope, standard deviation, sample size, and more. Students will then see theoretical distributions of the slope and intercept and how they compare to the histograms generated by the simulated linear regression lines.
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  • This in-class demonstration combines real world data collection with the use of the applet to enhance the understanding of sampling distribution. Students will work in groups to determine the average date of their 30 coins. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. The idea here is that students will remember what they physically did to create the histogram and, therefore, have a better understanding of sampling distributions.
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  • A joke about the need for students to explain how they arrived at the answers they provide on exams.

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  • This site funded by the Kaiser Family Foundation provides information on health care and demographics for the 50 U.S. states. Users can use interactive maps or search by particular characteristics for each state. Tables can be created and copied and there is also direct data download (in Excel format) from this site. The site includes data on median income, gender, ethnicity, medical and drug spending, HIV/AIDS rates, and over 500 other variables at the state level
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  • Normality is a myth; there never has, and never will be, a normal distribution. A quote by Irish statistician and econometrician Roy C. Geary (1896 - 1983) found in "Biometrika" volume 34, 1947, page 241.

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  • I abhor averages. I like the individual case. A man may have six meals one day and none the next, making an average of three meals per day, but that is not a good way to live. A quote by American Supreme Court Justice Louis Dembitz Brandeis (1856 - 1951) as quoted in "Brandeis: A Free Man's Life" by Alpheus Thomas Mason Viking Press, 1946; page 145). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • Those who fear muddy feet will never discover new paths. A quote by American writer and teacher Paul Eldridge (1888- 1982) found in his book "Maxims for a Modern Man" (Thomas Yoseloff Publishing, 1965). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

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  • Variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions which we know as disease. A quote by Canadian physician and medical educator Sir William Osler (1859 - 1919). The quote appears in William Osler: Aphorisms from his bedside teachings and writings, (Henry Schuman; 1950, page 104).

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  • Do not put your faith in what statistics say until you have carefully considered what they do not say. A quote by English professor William Whyte Watt (1912 - 1996) in his book "An American Rhetoric" (Rinehart and Co.; 1958 3rd edition, page 382).

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