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 Probability and Statistics release 25.63
FULL VERSION
CONTENTS
  • Part I Probability
    • Counting Principles and Probability
      • Counting Principles
        • Permutations
          • Permutations of n Elements
          • Permutations of n Elements Taken r at a Time
          • Distinguishable Permutations
        • Combinations
        • Fundamental Counting Principles
      • Probability
        • Basic Probability Concepts
        • Venn Diagram
        • Conditional Probability and Multiplication Theorem
        • Addition Theorem
        • Complementation Theorem
        • Theorem of Total Probability
        • Bayes Theorem
    • Random Variables
      • Discrete Random Variables
        • Univariate Case
          • Probability Mass Function
          • Cumulative Distribution Function
          • Expected Value
          • Variance and Standard Deviation
          • Moments
        • Bivariate Case
          • Joint Probability Mass Function
          • Joint Cumulative Distribution Function
          • Marginal Probability Distributions
          • Conditional Probability Distribution
          • Independent Random Variables
          • Covariance and Correlation Coefficient
      • Continuous Random Variables
        • Univariate Case
          • Probability Density Function
          • Cumulative Distribution Function
          • Expected Value
          • Variance
          • Moments
        • Bivariate Case
          • Joint Probability Density Function
          • Joint Cumulative Distribution Function
          • Marginal Probability Distributions
          • Conditional Probability Density Function
          • Independent Random Variables
          • Covariance and Correlation Coefficient
    • Discrete Distributions
      • Uniform Distribution
      • Binomial Distribution
      • Poisson Distribution
    • Continuous Distributions
      • Uniform Distribution
      • Exponential Distribution
      • Normal Distribution
    • Distributions Related to the Normal
      • Chi-Square distribution
      • Student's t-distribution
      • Snedecor's F-distribution
      • Properties of the Sample Mean and Variance
  • Part II Statistics
    • Descriptive Statistics
      • Graphical Data Representation
        • Boxplot
        • Histogram
      • Measures of Location
        • Mean
        • Median
        • Mode
        • Quartiles
      • Measures of Spread
        • Interquartile Range
        • Range
        • Variance and Standard Deviation
    • Parameter Estimation
      • Point Estimations
      • Confidence Intervals
        • Confidence Intervals for a Mean
          • Two - Sided Confidence Interval for a Mean when the Variance is Known
          • One - Sided Confidence Interval for a Mean when the Variance is Known
          • Two - Sided Confidence Interval for a Mean when the Variance is Unknown
          • One - Sided Confidence Interval for a Mean when the Variance is Unknown
        • Confidence Intervals for a Difference of Two Means
          • Two - Sided Confidence Interval for a Difference of Means when Variances Are Known
          • One - Sided Confidence Interval for a Difference of Means when Variances Are Known
          • Two-Sided Confidence Interval for a Difference of Means when Variances Are Equal but Unknown
          • One-Sided Confidence Interval for a Difference of Means when Variances Are Equal but Unknown
        • Confidence Intervals for a Variance
          • Two - Sided Confidence Interval for a Variance when the Mean is Known
          • One - Sided Confidence Interval for a Variance when the Mean is Known
          • Two - Sided Confidence Interval for a Variance when the Mean is Unknown
          • One - Sided Confidence Interval for a Variance when the Mean is Unknown
        • Confidence Intervals for a Ratio of Variances
          • Two - Sided Confidence Interval for a Ratio of Variances
          • One - Sided Confidence Interval for a Ratio of Variances
        • Confidence Intervals for a Proportion
          • Two-Sided Confidence Interval for a Proportion: Large Sample
          • One-Sided Confidence Interval for a Proportion: Large Sample
          • Determining the Size of the Sample
        • Confidence Intervals for a Difference of Two Proportions
          • Two-Sided Confidence Interval for a Difference of Proportions
          • One-Sided Confidence Interval for a Difference of Proportions
    • Hypothesis Testing
      • General Principles
      • Tests for a Mean
        • Two-Tailed Test for a Mean when the Variance Is Known
        • One-Tailed Test for a Mean when the Variance Is Known
        • Two-Tailed Test for a Mean when the Variance Is Unknown
        • One-Tailed Test for a Mean when the Variance Is Unknown
      • Tests for a Difference of Two Means
        • Two-Tailed Test for a Difference of Means when Variances are Known
        • One-Tailed Test for a Difference of Means when Variances are Known
        • Two-Tailed Test for a Difference of Means when Variances Are Equal but Unknown
        • One-Tailed Test for a Difference of Means when Variances Are Equal but Unknown
      • Tests for a Variance
        • Two-Tailed Test for a Variance when the Mean Is Known
        • One-Tailed Test for a Variance when the Mean Is Known
        • Two-Tailed Test for a Variance when the Mean Is Unknown
        • One-Tailed Test for a Variance when the Mean Is Unknown
      • Tests for an Equality of Two Variances
        • Two-Tailed Test for an Equality of Two Variances
        • One-Tailed Test for an Equality of Two Variances
      • Tests for a Proportion
        • Two-Tailed Test for a Proportion: Large Sample
        • One-Tailed Test for a Proportion: Large Sample
      • Tests for a Difference of Two Proportions
        • Two-Tailed Test for a Difference of Proportions: Large Sample
        • One-Tailed Test for a Difference of Proportions: Large Sample
    • Linear Regression
      • The Method of Least Squares
      • The Simple Linear Regression Model
      • Estimating Parameters of a Simple Linear Regression Model
        • Estimating the Slope and Y-intercept of a Simple Linear Regression Model
        • Estimating the Variance of the Random Error Components
      • Confidence Interval for the Y-intercept of a Linear Regression
      • Confidence Interval for the Slope of a Linear Regression
      • Testing the Slope for Model Usefulness
      • Estimating the Mean Value of Y for a Given Value of X
      • Predicting One y-Value for a Given Value of x
      • The Coefficient of Determination
    • Analysis of Variance (ANOVA)
      • One - Way Analysis of Variance
        • The One - Way Analysis of Variance Technique
        • The Hypothesis Test in One - Way ANOVA
      • Two - Way Analysis of Variance
        • The Two - Way Analysis of Variance Technique
        • The Hypothesis Tests in Two Way ANOVA
ENTER Probability and Statistics ENTER Probability and Statistics
ENTER Probability and Statistics ENTER Probability and Statistics

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