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Descriptive Methods | |
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Distribution Tables: Discrete Data Bar Graphs Bivariate Data: Two-Way Tables | |
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A Quick Look at Distribution: Stem and Leaf Constructing a Simple Stem-and-Leaf Diagram | |
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Frequency Distributions: Histograms Rules for Breaking Data into Classes Cumulative Distribution | |
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Measures of Location or Central Tendency Sample Mean Sample Median | |
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Measures of Variability or Dispersion Sample Variance Sample Standard Deviation Sample Range Interquartile Range Finding the Sample Interquartile Range Multiple Data Sets | |
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Box Plots Constructing a Box Plot | |
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Introduction to Probability and Counting | |
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Interpreting Probablilities | |
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Tree Diagrams and Elementary Genetics Elementary Genetics | |
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Permutations and Combinations | |
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Multiplication Principle Guidelines for Using the Multiplication Principle | |
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Permutations of Indistinguishable Objects | |
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Combinations | |
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Probability and Problem Solving | |
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Venn Diagrams and the Axioms of Probability Venn Diagrams Axioms of Probability | |
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General Addition Rule | |
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Conditional Probability | |
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Diagnostic Tests and Relative Risk Relative Risk | |
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Independence | |
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The Multiplication Rule | |
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Bayes' Theorem | |
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Discrete Random Variables | |
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Discrete and Continuous Variables | |
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Discrete Density Functions and Expectation Expectation | |
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Cumulative Distribution Function | |
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Binomial Distribution Expected Value and Variance: Binomial Calculating Binomial Probabilities: Cumulative Distribution | |
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Poisson Distribution | |
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Continuous Random Variables | |
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Continuous Random Variables Expectation | |
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Cumulative Distribution Function | |
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Normal Distribution Properties of Normal Curves Standard Normal Distribution Standardization | |
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Normal Probability Rule and Medical Tables | |
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Inferences on the Mean | |
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Random Sampling and Randomization Simple Random Sampling Randomization | |
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Point Estimation of the Mean and Introduction to Interval Estimation: Central Limit Theorem Interval Estimation Central Limit Theorem | |
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Confidence Interval on the Population Mean and the T Distribution Properties of T Random Variables | |
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Introduction to Hypothesis Testing | |
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Testing Hypotheses on the Population Mean: T Test Preset Alpha Values | |
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Sample Size: Confidence Intervals and Power Sample Size: Hypothesis Testing | |
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Chi-Squared Distribution and Inferences on the Variance | |
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Chi-Squared Distribution and Interval Estimation of the Population Variance Confidence Interval on s2 | |
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Testing Hypotheses on the Population Variance | |
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Inferences on Proportions | |
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Point Estimation | |
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Interval Estimation of p | |
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Sample Size for Estimating p | |
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Hypothesis Testing on p | |
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Comparing Two Proportions: Estimation Confidence Interval on the Difference in Two Proportions | |
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Comparing Two Proportions: Hypothesis Testing Testing That the Null Value Is Zero: Pooled Test | |
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Comparing Two Means and Two Variances | |
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Comparing Two Means and Two Variances | |
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Comparing Variances: F Distribution Rule of Thumb Variance Comparison F Test for Comparing Variances: F Distribution | |
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Inferences on m1 - m2: Pooled T Interval Estimation of m1 - m2 Pooled T Tests | |
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Inferences on m1 - m2: Unequal Variances | |
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Inferences on m1 - m2: Paired T Paired T Test | |
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k-Sample Procedures: Introduction to Design | |
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One-Way Classification, Completely Random Design with Fixed Effects Data Format and Notation | |
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Paired and Multiple Comparisons Bonferroni T Tests: Paired Comparisons Duncan's Multiple Range Test A Note on Computing | |
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Random Effects | |
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Randomized Complete Blocks | |