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  • Statistics at Square One: Correlation and Regression

    This section of an online textbook discusses the correlation coefficient and illustrated it visually through graphs. It explains calculations as well as how scatter plots can describe data. It covers significance tests for relationships, the Spearman rank correlation and the regression equation. Exercises and answers are included.

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  • Statistics at Square One: Differences Between Percentages and Paired Alternatives

    This topic from an online textbook discusses standard error, confidence interval, and significance testing for a difference in percentages or proportions. It also covers paired alternatives and standard error of a total. Exercises and answers are also provided.

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  • Power of a Hypothesis Test

    This applet performs a hypothesis test for the mean of a single normal population, variance known. Users set the hypothesized mean, true mean, variance, and appropriate alternative hypothesis. The applet plots a representative distribution under the given values with power shaded in blue and significance level shaded in red.

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  • DIG Stats: Excel Guide for Making a 3-D Graph

    This tutorial explains in detail how to make a 3-D graph using the Chart Wizard in Excel.

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  • DIG Stats: Health Insurance Activity

    In this activity, students will perform a chi-squared test on the number of people with health insurance by age to determine whether there is a relationship between age and insurance coverage. Questions about the exercise and a link to the DIG Stats Online Chi-Squared Calculator are given. The data exist in Excel and text formats.

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  • Dataset: DIG Stats: Baseball Salaries Activity

    In this activity, students will calculate the mean, median, and mode of the salaries for the Angels and the Orioles baseball players. Questions about the exercise and links to Excel and TI-83 instructions. The data exists in Excel, TI-83, and text formats.

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  • DAU StatRefresher: Clustering Algorithms

    This interactive module helps students to understand the definition of and uses for clustering algorithms. Students will learn to categorize the types of clustering algorithms, to use the minimal spanning tree and the k-means clustering algorithm, and to solve exercise problems using clustering algorithms.

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  • DAU StatRefresher: Exponential Smoothing

    This interactive tutorial on Exponential Smoothing helps learners understand the use of exponential smoothing, define exponential smoothing, cite the merits and demerits of exponential smoothing, and solve exercise problems using exponential smoothing.

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  • DAU StatRefresher: Multiple Regression

    This tutorial on Multiple Regression helps students understand the definition, use the standard error of estimate, use rank correlation, and solve exercise problems using multiple regression.

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  • DAU StatRefresher: Distributions

    This tutorial on Distributions helps students understand the basic concept of probability distributions, recognize and use Binomial, Normal, Poisson, and Uniform Distributions, and solve exercise problems using probability distributions.

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