7.3 Statistics (also see 9.10) Cauchy's Inequality and the Least Squares Line, William Stenger, 6:1, 1975, 2-4 Random Charity: A Stochastic Sieving Problem and its Connection with the Euclidean Algorithm, Roland Engdahl and Karl Greger, 6:4, 1975, 4-9 Statistical Inference for the General Education StudentÑIt Can Be Done, Allen H. Holmes, Walter Sanders and John LeDuc, 8:4, 1977, 223-230 The Use of Sports Data for Integrating Topics in Introductory Statistics, Robert L. Heiny, 9:1, 1978, 28-33 Classroom Demonstration of a Confidence Interval, Wayne Andrepont and Peter Dickinson, 9:1, 1978, 34-36 The Range of the Standard Deviation, Lawrence Sher, 10:1, 1979, 33, C How Close are the Mean and the Median?, Stephen A. Book, 10:3, 1979, 202-204, C An Expected Value Problem, Harris S. Schultz, 10:4, 1979, 277-278, C Why n-1 in the Formula for the Sample Standard Deviation?, Stephen A. Book, 10:5, 1979, 330-333 Bounds for the Sum of Absolute Standard Scores, Lawrence Sher, 10:5, 1979, 351-353, C CorrelationÑA Vector Approach, Kenneth R. Kundert, 11:1, 1980, 52, C, 5.5 An Expected Value Problem Revisited, W. J. Hall, 11:3, 1980, 204-205 An Analytic Geometry Approach to the Least Squares Line of Best Fit, Stewart Venit and Richard Katz, 11:4, 1980, 270-272, C, 0.5 A Bound for Standard Scores, Lawrence Sher, 11:2, 1980, 334-335, C A Mean Generating Function, Jack C. Slay and J. L. Solomon, 12:1, 1981, 27-29, 5.1.2 Partial and Semipartial CorrelationÑA Vector Approach, John Huber, 12:2, 1981, 151-153, C Another Look at the Mean, Median, and Standard Deviation, Ruma Falk, 12:3, 1981, 207-208, C Bounds for the Ratio of the Arithmetic Mean to the Geometric Mean, M. Perisastry and V. N. Murty, 13:2, 1982, 160-161, C Nearness Relations Among Measures of Central Tendency and Dispersion: Part 1, Warren Page and V. N. Murty, 13:5, 1982, 315-326 Nearness Relations Among Measures of Central Tendency and Dispersion: Part 2, Warren Page and V. N. Murty, 14:1, 1983, 8-17 Another Proof of the Inequality (n^2)(sigma)^2 < (n^2/4)(R^2), V. N. Murty and M. Perisastry, 14:1, 1983, 61-63, C Interfractile Ranges, Warren Page, 14:2, 1983, 170-172, C Uncertainty in Science and Statistics, Clifford H. Wagner, 14:4, 1983, 360-363 Computer Simulations to Clarify Key Ideas of Statistics, Thomas Kersten, 14:5, 1983, 416-420 Some Breakthroughs in Statistical Methodology, Herbert Robbins, 15:1, 1984, 25-29 On the Mean and Standard Deviation of a Random Sample, Vedula N. Murty, 15:1, 1984, 60-62 A Geometrical Interpretation of the Weighted Mean, Larry Hoehn, 15:2, 1984, 135-139, 0.2, 0.4 The Electronic Spreadsheet and Mathematical Algorithms, Deane E. Arganbright, 15:2, 1984, 148-157, 4.1, 5.4.1, 9.6 On the Natural Density of the Niven Numbers, Robert E. Kennedy and Curtis N. Cooper, 15:4, 1984, 309-312, 9.3 Accurate Computation of Variance, Jerry A. Roberts, 16:2, 1985, 149-150 Instances of Simpson's Paradox, Thomas R. Knapp, 16:3, 1985, 209-211, C, 0.2 The Probability that the "Sum of the Rounds" Equals the "Round of the Sum", Roger B. Nelsen and James E. Schultz, 18:5, 1987, 390-396, 7.2, 9.10 Should Mathematicians Teach Statistics?, David S. Moore, 19:1, 1988, 3-7, 1.2 Should Mathematicians Teach Statistics? (Response), A. Blanton Godfrey, 19:1, 1988, 8-32, 1.2 No! But Who Should Teach Statistics?, Judith Tanur, 19:1, 1988, 8-32, 1.2 Statistics Teachers need Experience With Data, R. Gnanadesikan and J. R. Kettenring, 19:1, 1988, 8-32, 1.2 The Mathematicians' Statistics Has a Subsidiary Role, Barbara A. Bailar, 19:1, 1988, 8-32, 1.2 Growth and Advances in Statistics, Frederick Mosteller, 19:1, 1988, 8-32, 1.2 Statistician, Examine Thyself, Gudmund R. Iversen, 19:1, 1988, 8-32, 1.2 It's Not "By Whom" But Rather "How", John E. Freund, 19:1, 1988, 8-32, 1.2 The Need for Good Teaching of Statistics, Henry L. Alder, 19:1, 1988, 8-32, 1.2 Let the Experts Teach and Judge, David L. Hanson, 19:1, 1988, 8-32, 1.2 Who Teachers What to Whom?, Michail Reed, 19:1, 1988, 8-32, 1.2 What Should the Introductory Statistics Course Contain?, Gerald J. Hahn, 19:1, 1988, 8-32, 1.2 Mathematics is Only One Tool that Statisticians Use, Ronald D. Snee, 19:1, 1988, 8-32, 1.2 Reaction to Responses to "Should Mathematicians Teach Statistics?", David S. Moore, 19:1, 1988, 32-34, 1.2 Readers' Responses to the January 1988 Forum: "Should Mathematicians Teach Statistics?", Joseph B. Kadane and William A. Golomsky and Daniel A. Sankowsky and Benjamin M. Perles, 19:2, 1988, 164-165, 1.2 Theory, Simulation and Reality, Peter Flusser, 19:3, 1988, 210-222, 9.10, 7.2 Using Leverage and Influence to Introduce Regression Diagnostics, David C. Hoaglin, 19:5, 1988, 387-401 Conditional Expectations and the Correlation Function, Barthel W. Huff, 20:1, 1989, 55-57, C A Note on Pascal's Triangle and Simple Random Sampling, Tommy Wright, 20:1, 1989, 59-66 Using Median Splits to Motivate Learning, David P. Doane, 20:3, 1989, 228-229, C Sensitive Questions and Randomized Response Techniques, Kenneth R. Kundert, 20:5, 1989, 409-411, C The Longest Run of Heads, Mark F. Schilling, 21:3, 1990, 196-207 Bernoulli Trials and the Central Limit Theorem, David P. Kraines and Vivian Y. Kraines and David A. Smith, 21:5, 1990, 415-416, C Using Simulation to Study Linear Regression, LeRoy A. Franklin, 23:4, 1992, 290-295, 9.10 Least Squares and Quadric Surfaces, Donald Teets, 24:3, 1993, 243-244, C, 5.7.1, 5.6.2 Determining Sample Sizes for Monte Carlo Integration, David Neal, 24:3, 1993, 254-262, C, 5.2.2, 9.10 Quadratic Confidence Intervals, Neil C. Schwertman and Larry R. Dion, 24:5, 1993, 453-457, C Chebyshev's Theorem: A Geometric Approach, Pat Touhey, 26:2, 1995, 139-141, C MAD Property of Medians: An Induction Proof, Eugene F. Schuster, 26:5, 1995, 387-389, C, 0.9 Will the Real Best Fit Curve Please Stand Up?, Helen Skala, 27:3, 1996, 220-223, C, 5.7.1 What is the Margin of Error of a Poll?, Bennett Eisenberg, 28:3, 1997, 201-203, C StudentÕs t and Crackers, Paul M. Sommers, 30:1, 1999, 32-34 Recommendations for Teaching the Reasoning of Statistical Inference, Allan Rossman and Beth Chance, 30:4, 1999, 297-305, 1.1 Getting Normal Probability Approximations Without Using Normal Tables, Peter Thompson and Lorrie Lendvoy, 31:1, 2000, 51-54, C The Super Bowl Theory: Fourth and Long, Paul Sommers, 31:3, 2000 The Geometry of Statistics, David Farnsworth, 31:3, 2000, 200-204 t-Probabilities as Finite Sums, Neil Eklund, 31:3, 2000, 217-218, C The Lognormal Distribution, Brian E. Smith and Francis Merceret, 31:4, 2000, 259-261 Food and Drug Interaction: What Role Does Statistics Play?, Thomas Bradstreet, 31:4, 2000, 268-273 Well-Rounded Figures, Yves Nievergelt, 32:1, 2001, 30-32, 9.6 The Average Speed on the Highway, Larry Clevenson, Mark Schilling, Ann Watkins, and William Watkins, 32:3, 2001, 169-171 Is Presidential Greatness Related to Height?, Paul M. Sommers, 33:1, 2002, 14-16 Symmetric or Skewed?, Joseph G. Eisenhauer, 33:1, 2002, 48-51, C Winning Games in Canadian Football: A Logistic Regression Analysis, Keith A. Willoughby, 33:3, 2002, 215-220 Almost-Binomial Random Variables, Peter Thompson, 33:3, 2002, 235-237, C Chasing Hank AaronÕs Home Run Record, Steven P. Bisgaier, Benjamin S. Bradley, Peter D. Harwood, and Paul M. Sommers, 33:4, 2002, 293-295 Observations on the Indeterminacy of the Sample Correlation Coefficient, Owen Byer, 33:4, 2002, 316-318, C BaseballÕs All-Stars: Birthplace and Distribution, Paul M. Sommers, 34:1, 2003, 24-30 A Calculus Theorem Motivated by a Statistics Problem, David L. Farnsworth, 35:2, 2004, 126-129, C FFF. Teenagers, Sex and Accidents, Joseph G. Eisenhauer, 35:3, 2004, 213-214, F A Quick Proof that the Least Squares Formulas Give a Local Minimum, W. M. Dunn III, 36:1, 2005, 64-65, C, 5.7.1 A Painless Approach to Least Squares, Eric S. Key, 36:1, 2005, 65-67, C A Recursive Formula for Moments of a Binomial Distribution, Arpad Benyi and Saverio M. Manago, 36:1, 2005, 68-72, C The Sample Correlation Coefficient from a Linear Algebra Perspective, C. Ray Rosentrater, 37:1, 2006, 47-50, C, 4.3 An Elegant Mode for Determining the Mode, D. S. Broca, 37:2, 2006, 134-137, C FFF #252. A snafu, Kenneth Schilling, 37:4, 2006, 290, F Distortion of average class size: The Lake Wobegon effect, Allen Schwenk, 37:4, 2006, 293-296, C More Mathematics in the Bedroom: A Paradoxical Probability, Paul K. Stockmeyer, 38:5, 2007, 339-344, 9.4 A Waiting-Time Surprise, Richard Parris, 39:1, 2008, 59-63, C The Pearson and Cauchy-Schwarz Inequalities, David Rose, 39:1, 2008, 64, C, 5.5, 9.5