Consortium for the Advancement of Undergraduate Statistics Education

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Consortium for the Advancement of Undergraduate Statistics Education Collection Resources (32)

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The Central Limit Theorem
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The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform).

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
02/16/2011
Confidence Intervals
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The applets in this section of Statistical Java allow you to see how levels of confidence are achieved through repeated sampling. The confidence intervals are related to the probability of successes in a Binomial experiment.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C.Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S.Dorai-Raj
T.Robinson
Date Added:
02/16/2011
Control Charts
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The applets in this section allow you to see how the common Xbar control chart is constructed with known variance. The Xbar chart is constructed by collecting a sample of size n at different times t.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Doria-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
02/16/2011
Correlation
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The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
02/16/2011
Data Analysis
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The applet in this section allows for simple data analysis of univariate data. Users can either generate normal or uniform data for k samples or copy and paste data from another source to a text box. A univariate analysis is performed for all k samples.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C. Anderson-Cook, S. Dorai-Raj, T. Robinson, Virginia Tech Department of Statistics
Date Added:
02/16/2011
Exponential Probabilities
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The applet in this section allows you see how probabilities are determined from the exponential distribution. The user determines the mean of the distribution and the limits of probability. Three different probability expressions are available.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
02/16/2011
Introduction to Minitab
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This laboratory introduces students to the basics of the Minitab software. Students make use of a basic example (water consumption and temperature) to introduce students to manipulation of data, calculation of descriptive statistics, and creation of histograms.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Ginger Holmes Rowell
Rowell, Ginger
Date Added:
02/16/2011
Learning Objectives for Introductory Statistics
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This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Jeff Thompson, Pam Arroway, Roger Woodard, North Carolina State University
Date Added:
02/16/2011
Mouse Experiment
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This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Dennis Pearl
Tom Santner
Date Added:
02/16/2011
Normal Distribution
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The applets in this section allow users to see how probabilities and quantiles are determined from a Normal distribution. For calculating probabilities, set the mean, variance, and limits; for calculating quantiles, set the mean, variance, and probability.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C. Anderson-Cook, S. Dorai-Raj, T. Robinson, Virginia Tech Department of Statistics
Date Added:
02/16/2011
Power Applet
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The applets in this section of Statistical Java address Power. Users can perform one or two tailed tests for proportions or means for one or two samples. Set the parameters and drag the mouse across the graph to see how effect size affects power.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C.Anderson-Cook
Doria-Raj, S.
Robinson, T.
S.Dorai-Raj
T.Robinson
Date Added:
02/16/2011
Probability Distributions
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This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C.Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S.Dorai-Raj
T.Robinson
Date Added:
02/16/2011
Regression
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This applet from Statistical Java allows the user to generate bivariate data for analysis with simple linear regression. The page describes the equations used to generate the data and estimate the regression lines.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C.Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S.Dorai-Raj
T.Robinson
Date Added:
02/16/2011
Sampling from a Real Estate Database
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This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their findings.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Roger Woodard
Woodard, Roger
Date Added:
02/16/2011
Star Library: An Unusual Episode
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Dawson (1995) presented a data set giving a population at risk and fatalities for an “unusual episode” (the sinking of the ocean liner Titanic) and discussed the use of the data set in a first statistics course as an elementary exercise in statistical thinking, the goal being to deduce the origin of the data. Simonoff (1997) discussed the use of this data set in a second statistics course to illustrate logistic regression. Moore (2000) used an abbreviated form of the data set in a chapter exercise on the chi-square test. This article describes an activity that illustrates contingency table (two-way table) analysis. Students use contingency tables to analyze the “unusual episode” data (from Dawson 1995) and attempt to use their analysis to deduce the origin of the data. The activity is appropriate for use in an introductory college statistics course or in a high school AP statistics course.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Mary Richardson, Grand Valley State University
Date Added:
02/16/2011
Star Library: Breaking the Code - A Graphical Exploration Using Bar Charts
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The activity begins with an explanation of the Caesar Shift for message encryption (Singh, 1999). The Caesar Shift is a translation of the alphabet; for example, a five-letter shift would code the letter a as f, b as g, … z as e. We describe a five-step process for decoding an encrypted message. First, groups of size 4 construct a frequency table of the letters in two lines of a coded message. Second, students construct a bar chart for a reference message of the frequency of letters in the English language. Third, students create a bar chart of the coded message. Fourth, students visually compare the bar chart of the reference message (step 2) to the bar chart of the coded message (step 3). Based on this comparison, students hypothesize a shift. Fifth, students apply the shift to the coded message.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
John Gabrosek and Michael E. Schuckers, Grand Valley State University and West Virginia University
Date Added:
02/16/2011
Star Library: Counting Eights: A First Activity in the Study and Interpretation of Probability
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Students explore the definition and interpretations of the probability of an event by investigating the long run proportion of times a sum of 8 is obtained when two balanced dice are rolled repeatedly. Making use of hand calculations, computer simulations, and descriptive techniques, students encounter the laws of large numbers in a familiar setting. By working through the exercises, students will gain a deeper understanding of the qualitative and quantitative relationships between theoretical probability and long run relative frequency. Particularly, students investigate the proximity of the relative frequency of an event to its probability and conclude, from data, that the dispersion of the relative frequency diminishes on the order .

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Hartlaub, Bradley
Jones, Brian D.
Date Added:
02/16/2011
Star Library: Histogram Sorting
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This activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), that not all histograms are easy to classify, that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.).

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Garfield, Joan
Date Added:
02/16/2011
Star Library: Random Rendezvous
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This activity leads students to appreciate the usefulness of simulations for approximating probabilities. It also provides them with experience calculating probabilities based on geometric arguments and using the bivariate normal distribution. We have used it in courses in probability and mathematical statistics, as well as in an introductory statistics course at the post-calculus level.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Allan J. Rossman and Beth L. Chance
Chance, Beth, Cal Poly State University
Rossman, Allan, Dickinson College
Date Added:
02/16/2011
Star Library: Rectangularity
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This article describes an interactive activity illustrating sampling distributions for means, properties of confidence intervals, properties of hypothesis testing, confidence intervals for means, and hypothesis tests for means. Students generate and analyze data and through simulation explore these concepts. The activity is completed in three parts. The three parts of the activity can be used in sequence or they can be used individually as Š—“stand aloneŠ— activities. This allows the educator flexibility in utilizing the activity. Part I illustrates the sampling distribution of the sample mean. Part II illustrates confidence intervals for the population mean. Part III illustrates hypothesis tests for the population mean. This activity is appropriate for use in an introductory college or high school AP statistics course.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Curtiss, Phyllis
Gabrosek, John
Reischman, Diann
Richardson, Mary
Date Added:
02/16/2011
Star Library: Regression - Residuals - Why?
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As teachers of statistics, we know that residual plots and other diagnostics are important to deciding whether or not linear regression is appropriate for a set of data. Despite talking with our students about this, many students might believe that if the correlation coefficient is strong enough, these diagnostic checks are not important. The data set included in this activity was created to lure students into a situation that looks on the surface to be appropriate for the use of linear regression but is instead based (loosely) on a quadratic function.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Jacqueline B. Miller
Miller, Jacqueline B.
Date Added:
02/16/2011
Star Library: Regression on the Rebound
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This activity is an advanced version of the “Keep your eyes on the ball” activity by Bereska, et al. (1999). Students should gain experience with differentiating between independent and dependent variables, using linear regression to describe the relationship between these variables, and drawing inference about the parameters of the population regression line. Each group of students collects data on the rebound heights of a ball dropped multiple times from each of several different heights. By plotting the data, students quickly recognize the linear relationship. After obtaining the least squares estimate of the population regression line, students can set confidence intervals or test hypotheses on the parameters. Predictions of rebound length can be made for new values of the drop height as well. Data from different groups can be used to test for equality of the intercepts and slopes. By focusing on a particular drop height and multiple types of balls, one can also introduce the concept of analysis of variance.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Trent D. Buskirk and Linda J. Young, University of Nebraska-Lincoln and University of Nebraska-Lincoln
Date Added:
02/16/2011
Star Library: Sampling Distributions of the Sample Mean and Sample Proportion
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In these activities designed to introduce sampling distributions and the Central Limit Theorem, students generate several small samples and note patterns in the distributions of the means and proportions that they themselves calculate from these samples.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Andrews, Douglas
Date Added:
02/16/2011
Star Library: Simulating Size and Power Using a 10-Sided Die
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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.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Blankenship, Erin
Young, Linda J., 1952-
Date Added:
02/16/2011
Star Library: The Role of Probability in Discrimination Cases
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An important objective in hiring is to ensure diversity in the workforce. The race or gender of individuals hired by an organization should reflect the race or gender of the applicant pool. If certain groups are under-represented or over-represented among the employees, then there may be a case for discrimination in hiring. On the other hand, there may be a number of random factors unrelated to discrimination, such as the timing of the interview or competition from other employers, that might cause one group to be over-represented or under-represented. In this exercise, we ask students to investigate the role of randomness in hiring, and to consider how this might be used to help substantiate or refute charges of discrimination.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Higgins, James J.
James J. Higgins
Date Added:
02/16/2011
Star Library: What Makes the Standard Deviation Larger or Smaller?
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The activity is designed to help students develop a better intuitive understanding of what is meant by variability in statistics. Emphasis is placed on the standard deviation as a measure of variability. As they learn about the standard deviation, many students focus on the variability of bar heights in a histogram when asked to compare the variability of two distributions. For these students, variability refers to the Š—“variationŠ— in bar heights. Other students may focus only on the range of values, or the number of bars in a histogram, and conclude that two distributions are identical in variability even when it is clearly not the case. This activity can help students discover that the standard deviation is a measure of the density of values about the mean of a distribution and to become more aware of how clusters, gaps, and extreme values affect the standard deviation.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
delMas, Robert C.
Date Added:
02/16/2011
Star Library: What is the Shelf Life?
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The Food and Drug Administration requires pharmaceutical companies to establish a shelf life for all new drug products through a stability analysis. This is done to ensure the quality of the drug taken by an individual is within established levels. The purpose of this out-of-class project or in-class example is to determine the shelf life of a new drug. This is done through using simple linear regression models and correctly interpreting confidence and prediction intervals. An Excel spreadsheet and SAS program are given to help perform the analysis.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Bilder, Christopher R.
Christopher R. Bilder
Date Added:
02/16/2011
Star Library: What is the Significance of a Kiss?
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This article describes an interactive activity illustrating general properties of hypothesis testing and hypothesis tests for proportions. Students generate, collect, and analyze data. Through simulation, students explore hypothesis testing concepts. Concepts illustrated are: interpretation of p-values, type I error rate, type II error rate, power, and the relationship between type I and type II error rates and power. This activity is appropriate for use in an introductory college or high school statistics course.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Curtiss, Phyllis
Gabrosek, John
John Gabrosek
Mary Richardson
Phyllis Curtiss
Richardson, Mary
Date Added:
02/16/2011
Star Library: Which Paper Towel is More Absorbent?
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This group activity focuses on conducting an experiment to determine which of two brands of paper towels are more absorbent by measuring the amount of water absorbed. A two-sample t-test can be used to analyze the data, or simple graphics and descriptive statistics can be used as an exploratory analysis. Students are asked to think about design issues, and to write a short report stating their results and conclusions, along with an evaluation of the experimental design.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Christopher J. Malone, Christopher R. Bilder, Deborah J. Rumsey, John E. Boyer, Kansas State University, Ohio State University, Oklahoma State University
Date Added:
02/16/2011
The T Distribution
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This applet allows the user to adjust the degrees of freedom of the T Distribution with a slider or manual input. The applet allows the user to fix the x and or y axes. The user immediately sees how this affects the shape of the graph.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C.Anderson-Cook, S.Dorai-Raj, T.Robinson, Virginia Tech Department of Statistics
Date Added:
02/16/2011
T Probabilities
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The applet in this section allows you to see how the T distribution is related to the Standard Normal distribution by calculating probabilities. The T distribution is primarily used to make inferences on a Normal mean when the variance is unknown.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
Date Added:
02/16/2011
The Weibull Distribution
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This applet allows the user to adjust the alpha (rate) and the beta (scale) parameters of the Gamma distribution with a slider or manual input. The user can also indicate a model (density, hazard, or reliability).

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C.Anderson-Cook, S.Dorai-Raj, T.Robinson, Virginia Tech Department of Statistics
Date Added:
02/16/2011