INE 313 • Midterm • Statistical Decision Making

Axioms of Probability

Conditional Probability

Total Probability Rule

Bayes Rule

Independence

Random Variables

Probability Mass Function (PMF) for Discrete RV

Cumulative Distribution Function for Discrete RV

Probability Density Function (PDF) for Continuous RV

Cumulative Distribution Function (CDF) for Continuous RV

Discrete Joint Random Variables

Marginal PMF and CDF for Discrete Joint RV

Conditional PMF and CDF for Discrete Joint RV

Continuous Joint Random Variables

Marginal PDF and CDF for Continuous Joint RV

Conditional PDF and CDF for Continuous Joint RV

Expected Value for Discrete RV

Variance for Discrete RV

Expected Value for Continuous RV

Variance for Continuous RV

Expected Value for Discrete Joint RV

Variance for Discrete Joint RV

Conditional Expectation for Discrete Joint RV

Expected Value and Variance for Continuous Joint RV

Conditional Expectation for Continuous Joint RV

Introduction

Frequency Distribution

Example 1

Relative Frequency Distribution

Example 2

Cumulative Frequency Distribution

Example 3

Frequency Histogram

Measures of Central Tendancy

Example 4

Measures of Dispersion

Example 5

Example 6

Example 7

Skewness and Kurtosis

Stem and Leaf Diagram

Example 8

Example 9

Box and Whisker Plot

Example 10

Comparing Boxplots

Example 11

Example 12

Probability Basics 1

Probability Basics 2

Probability Basics 3

Probability Basics 4

Probability Basics 5

Probability Basics 6

Introduction to Statistics 1

Introduction to Statistics 2

Introduction to Statistics 3

Introduction to Statistics 4

Introduction to Statistics 5

Introduction to Statistics 6

Introduction to Statistics 7

Reading Z Table - Option 1

Reading Z Table - Option 2

Reading T Table

Reading Chi Table

Reading F Table

Sample Mean

Sample Variance

Example 1

Central Limit Theorem

Example 2

Example 3

Example 4

Example 5

Example 6

Introduction

Unbiased Estimators

Example 1

Variance of an Estimator

Consistent Estimator 1

Method of Moments

Example 2

Example 3

Method of Maximum Likelihood

Example 4

Example 5

Introduction

Table Values

Confidence Interval on the Mean of Normal Distribution (Sigma known)

Example 1

Example 2

Example 3

Confidence Interval on the Mean of Normal Distribution (sigma unknown)

Example 1

Example 2

Confidence Interval for Population Proportion

Example 1

Example 2

Confidence Interval the Variance of Normal Distributions

Example 1

Example 2

Example 3

Prediction Interval for Means

Example 1

Example 2

Tolerance Intervals for Means

Example 1

Example 2

Central Limit Theorem 1

Central Limit Theorem 2

Central Limit Theorem 3

Central Limit Theorem 4

Central Limit Theorem 5

Central Limit Theorem 6

Point Estimation 1

Point Estimation 2

Point Estimation 3

Point Estimation 4

Point Estimation 5

Point Estimation 6

C.I. of Mean (Known Variance) 1

C.I. of Mean (Known Variance) 2

C.I. of Mean (Known Variance) 3

C.I. of Mean (Unknown Variance) 1

C.I of Mean (Unknown Variance) 2

C.I. of Mean (Unknown Variance) 3

C.I. of Proportion 1

C.I. of Proportion 2

C.I. of Variance 1

C.I. of Variance 2

C.I. of Variance 3

Prediction Interval for Means 1

Prediction Interval for Means 2

Tolerance Interval for Means 1

Tolerance Interval for Means 2