Data Analytics

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Using Statistics

Percentiles and Quartiles

Measures of Central Tendency

Measures of Variability

Grouped Data and the Histogram

Skewness and Kurtosis

Relations between the Mean and Standard Deviation

Methods of Displaying Data

Exploratory Data Analysis

Using the Computer

Expected Values of Discrete Random Variables

Sum and Linear Composite of Random Variables

Bernoulli Random Variable

The Binomial Random Variable

The Geometric Distribution

The Hyper geometric Distribution

The Poisson Distribution

Continuous Random Variables

Uniform Distribution

The Exponential Distribution

Normal distribution

Sample Statistics as Estimators of Population Parameters

Sampling Distributions

Estimators and Their Properties

Degrees of Freedom

The Template

Confidence Interval for the Population Mean When the Population Standard Deviation is Known

Confidence Intervals for m When s is Unknown - The t Distribution

Large-Sample Confidence Intervals for the Population Proportion p

Confidence Intervals for the Population Variance

Sample Size Determination

The Templates

The Concept of Hypothesis Testing

Computing the p-value

The Hypothesis Test

Pre-Test Decisions

Paired-Observation Comparisons

A Test for the Difference between Two Population Means UsingIndependent Random Samples

A Large-Sample Test for the Difference between Two Population Proportions

The F Distribution and a Test for the Equality of Two Population Variances

The Hypothesis Test of Analysis of Variance

The Theory and Computations of ANOVA

The ANOVA Table and Examples

Further Analysis

Models, Factors, and Designs

Two-Way Analysis of Variance

Blocking Designs

Basic Definitions: Events, Sample Space, and Probabilities

Basic Rules for Probability

Conditional Probability

Independence of Events

Combinatorial Concepts

The Law of Total Probability and Bayes’ Theorem

Joint Probability Table

Using the Computer

Basic Rules for Probability

Conditional Probability

Independence of Events

Combinatorial Concepts

The Law of Total Probability and Bayes’ Theorem

Joint Probability Table

Using the Computer

The Simple Linear Regression Model

Estimation: The Method of Least Squares

Error Variance and the Standard Errors of Regression Estimators

Correlation

Hypothesis Tests about the Regression Relationship

How Good is the Regression?

Analysis of Variance Table and an F Test of the Regression Model

Residual Analysis and Checking for Model Inadequacies

Use of the Regression Model for Prediction

The Solver method of Regression.

Estimation: The Method of Least Squares

Error Variance and the Standard Errors of Regression Estimators

Correlation

Hypothesis Tests about the Regression Relationship

How Good is the Regression?

Analysis of Variance Table and an F Test of the Regression Model

Residual Analysis and Checking for Model Inadequacies

Use of the Regression Model for Prediction

The Solver method of Regression.

Using Statistics

The k-Variable Multiple Regression Model

The F Test of a Multiple Regression Model

How Good is the Regression

Tests of the Significance of Individual Regression Parameters

Testing the Validity of the Regression Model

Using the Multiple Regression Model for Prediction