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Dr B's No Bull Guide

to Applied Statistics 101

Bryan Aguiar

Want to pass your statistics class? This guide will help you do just that.

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About

About

About the Book

Applied statistics comprises of descriptive statistics and the application of inferential statistics. This guide includes instructions for MS Excel 2010 or newer on MS Windows and a TI 83 or TI84 calculator.

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License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

Author

About the Author

Bryan Aguiar

I earned a BS in Business Administration from Husson College, a Master of Education in Curriculum and Instruction from South Dakota State University, a Master of Business Administration from Troy State University, a Master of Science in Data Analytics from Western Governors University, and a Doctor of Business Administration from Argosy University. I love to learn!

I started my teaching career as an adjunct instructor in 1996 at Oglala Lakota College, in Rapid City, South Dakota. I have been an adjunct instructor at the University of Phoenix, Webster University, the University of Maryland University College, Colorado State University – Global, and the Walton College of Business at the University of Arkansas. I have taught undergraduate courses in accounting, economics, leadership, management, marketing, organizational behavior, statistics, supervision, and supply chain management. I have taught graduate courses in accounting, business strategy, economics, and statistics.

Prior to my teaching career, I served twenty years in the United States Air Force. I retired as a Senior Master Sergeant (E-8) serving as a Munitions Systems Superintendent at Air Combat Command Headquarters.  I have been stationed in Maine, Nevada, New Mexico, South Dakota, and Virginia in the states and Germany, Turkey, and Saudi Arabia overseas. Prior to joining the Air Force, I was a grinder / burner at the Electric Boat hull-fabrication and outfitting facility of General Dynamics in Quonset Point, Rhode Island. There I had the opportunity to work on the lead submarine of the Ohio-class submarines, the USS Ohio.

Contents

Table of Contents

Introduction

  1. Populations and Samples
  2. Descriptive Statistics
  3. Inferential Statistics
  4. Summary

Variables

  1. Independent and Dependent Variables
  2. Quantitative Variables
  3. Qualitative Variables
  4. Comparing Quantitative & Qualitative Variables
  5. Levels of Measurement

Data Collection & Organization

  1. Research
  2. Conditions to Establish Causality
  3. Research Design
  4. Sampling
  5. Organizing Data

Descriptive Statistics - Numerical

  1. Univariate Descriptive Statistics
  2. Bivariate Descriptive Statistics

Descriptive Statistics - Numerical Examples with MS Excel

Descriptive Statistics - Numerical Examples with TI Calculator

Descriptive Statistics - Numerical Examples Manually

Descriptive Statistics - Numerical Examples with Python

Descriptive Statistics - Numerical Examples with SAS

  1. TBA

Descriptive Statistics - Visual

  1. Univariate Visual Displays
  2. Bivariate Visual Displays

Descriptive Statistics - Visual Examples with MS Excel

Descriptive Statistics - Visual Examples with TI Calculator

Descriptive Statistics - Visual Examples Manually

  1. TBA

Descriptive Statistics - Visual Examples with Python

  1. TBA

Descriptive Statistics - Visual Examples with SAS

  1. TBA

Probability

Probability Distributions

Discrete Probability Distributions

  1. Uniform Distribution
  2. Binomial Distribution
  3. Poisson Distribution

Continuous Probability Distributions

  1. Uniform Distribution
  2. Exponential Distribution
  3. Normal Distribution
  4. Student t Distribution
  5. Chi-Square Distribution
  6. F Distribution
  7. Binomial Approximations for Counts and Proportions

Continous Probability Distributions Examples with MS Excel

  1. Normal Distribution

Continuous Probability Distributions Examples with TI Calculator

  1. Normal Distribution

Continuous Probability Distributions Examples Manually

  1. Uniform Distribution
  2. Normal Distribution

Inverse Normal Distribution

Sampling Distribution

  1. Central Limit Theorem for Mean
  2. Central Limit Theorem for Proportions
  3. Standard Deviation versus Standard Error

Confidence Intervals

Confidence Intervals Examples with MS Excel

  1. Confidence Intervals for Unknown Population Mean and Known Population Standard Deviation
  2. Confidence Intervals for Unknown Population Mean and Unknown Population Standard Deviation
  3. Confidence Intervals for Unknown Population Proportion

Confidence Intervals Examples with TI Calculator

  1. Confidence Intervals for Unknown Population Mean with Known Population Standard Deviation
  2. Confidence Intervals for Unknown Population Mean with Unknown Population Standard Deviation
  3. Confidence Intervals for Unknown Population Proportion

Confidence Intervals Examples Computed Manually

  1. Confidence Intervals for Unknown Population Mean and Known Population Standard Deviation
  2. Confidence Intervals for Unknown Population Mean and Unknown Population Standard Deviation
  3. Confidence Intervals for Unknown Population Proportion

Null Hypothesis Significance Testing (NHST)

  1. Hypothesis Testing Steps

One Sample Hypothesis Testing

One Sample Hypothesis Testing Examples Using MS Excel

  1. One-tailed Hypothesis testing for a mean (σ is known)
  2. Two-tailed Hypothesis testing for a mean (σ is known)
  3. Two-tailed Hypothesis testing for a mean (σ is not known)

One Sample Hypothesis Testing Examples Using TI Calculator

  1. One-tailed Hypothesis testing for a mean (σ is known)
  2. Two-tailed Hypothesis testing for a mean (σ is known)
  3. Two-tailed Hypothesis testing for a mean (σ is not known)

One Sample Hypothesis Testing Examples Manually

  1. TBA

Two Sample Hypothesis Testing

  1. Types
  2. Formulas

Two Sample Hypothesis Testing Examples Using MS Excel

  1. Independent (Unpaired) Samples
  2. Two independent proportions
  3. Dependent (Paired) Samples

Two Sample Hypothesis Testing Examples Using TI Calculator

  1. Independent (Unpaired) Samples
  2. Two independent proportions
  3. Dependent (Paired) Samples

Two Sample Hypothesis Testing Examples Manually

  1. Independent (Unpaired) populations, σ is unknown but assumed unequal
  2. Independent populations, σ is unknown but assumed equal
  3. Two independent proportions

Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA) Example Using MS Excel

Analysis of Variance (ANOVA) Example Using TI Calculator

Analysis of Variance (ANOVA) Example Manually

  1. TBA

Linear Regression

  1. Least-Squares Regression
  2. Model Evaluation Metrics
  3. Hypothesis Testing
  4. Residual Analysis
  5. Influential Observation

Linear Regression Examples with MS Excel

Linear Regression Examples with a TI Calculator

Linear Regression Examples Manually

  1. TBA

Chi-Square Test for Independence

Chi-Square Test for Independence Examples with MS Excel

  1. TBA

Chi-Square Test for Independence Examples with TI Calculator

Chi-Square Test for Independence Examples Manually

Glossary

Appendix

  1. Statistical Tables
  2. Adding the MS Excel Toolpak
  3. How to program INVT into the TI-83/TI-83 Plus Calculator

References

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