Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries

Length: 255 pages
Edition: 1
Language: English
Publisher: Statistics By Jim Publishing
Publication Date: 2020-08-13
ISBN-10: 1735431109
ISBN-13: 9781735431109
Sales Rank: #17189 (See Top 100 Books)

Learn Statistics Without Fear!

Build a solid foundation in data analysis. Be confident that you understand what your data are telling you and that you can explain the results to others! I’ll help you intuitively understand statistics by using simple language and deemphasizing formulas.

This guide starts with an overview of statistics and why it is so important. We proceed to essential statistical skills and knowledge about different types of data, relationships, and distributions. Then we move to using inferential statistics to expand human knowledge, how it fits into the scientific method, and how to design and critique experiments.

Learn the fundamentals of statistics.

Why is the field of statistics so vital in our data-driven society?
Interpret graphs and summary statistics.
Find relationships between different types of variables.
Understand the properties of data distributions.
Use measures of central tendency and variability.
Interpret correlations and percentiles.
Use probability distributions to calculate probabilities.
Learn about the normal and binomial distributions in depth.
Grasp the differences between descriptive and inferential statistics.
Use data collection methodologies properly and understand sample size considerations.
Design and critique scientific experiments—whether it’s your own or another researcher’s.
Free access to downloadable datasets to follow along with the examples.

About the Author

Jim Frost has extensive experience using statistical analysis in academic research and consulting projects. He’s been performing statistical analysis on-the-job for over 20 years. For 10 of those years, he was a statistical software company helping others make the most out of their data. Jim loves sharing the joy of statistics. In addition to writing books, he has a statistics website and writes a regular column for the American Society of Quality’s Statistics Digest.

Prepare for an Adventure!
The Importance of Statistics
    Draw Valid Conclusions
    Avoid Common Pitfalls
    Make an Impact in Your Field
    Protect Yourself with Statistics
    Statistics versus Anecdotal Evidence
    Organization of this Book
Data Types, Graphs, and Finding Relationships
    Quantitative versus Qualitative Data
    Continuous and Discrete Data
    Qualitative Data: Categorical, Binary, and Ordinal
    Next Steps
    Histograms in More Detail
    Skewed Distributions
    Identifying Outliers
    Multimodal Distributions
    Identifying Subpopulations
    Comparing Distributions between Groups
    Histograms and Sample Size
    Boxplots vs. Individual Value Plots
    Two -Way Contingency Tables
    Cautions About Graphing
    Graphing and Philosophy
    Summary and Next Steps
Summary Statistics and Relative Standing
    Percentiles
    Special Percentiles
    Calculating Percentiles Using Values in a Dataset
    Measures of Central Tendency
    Measures of Variability
    Comparing Summary Statistics between Groups
    Correlation
    Interpreting Correlation Coefficients
    Pearson’s Measures Linear Relationship
    Correlation Does Not Imply Causation
    How Strong of a Correlation is Considered Good?
    Summary and Next Steps
Probability Distributions
    Discrete Probability Distributions
    Types of Discrete Distribution
    Binomial and Other Distributions for Binary Data
    Modelling Flu Outcomes Over Decades
    Continuous Probability Distributions
    Normal Distribution in Depth
    Parameters of the Normal Distribution
    Population parameters versus sample estimates
    Properties of the Normal Distribution
    The Empirical Rule
    Standard Normal Distribution and Standard Scores
    Calculating Z-scores
    Using a Table of Z-scores
    Why the Normal Distribution is Important
    Summary and Next Steps
Descriptive and Inferential Statistics
    Descriptive Statistics
    Example of Descriptive Statistics
    Inferential Statistics
    Pros and Cons of Working with Samples
    Populations
    Subpopulations
    Population Parameters versus Sample Statistics
    Tools for Inferential Statistics
    Properties of Good Estimates
    Sample Size and Margins of Error
    Sampling Distributions of the Mean
    Confidence Intervals and Precision
    Random Sampling Methodologies
    Example of Inferential Statistics
    Summary and Next Steps
Statistics in Scientific Studies
    Step 1: Research Your Study Area
    Step 2: Operationalize Your Study
    Step 3: Data Collection
    Step 4: Statistical Analysis
    Step 5: Writing the Results
    Summary and Next Steps
Experimental Methods
    Types of Variables in Experiments
    Causation versus Correlation
    Confounding Variables
    Why Determining Causality Is Important
    Causation and Hypothesis Tests
    True Randomized Experiments
    Random Assignment
    Flu Vaccination Experiment
    Drawbacks of Randomized Experiments
    Quasi-Experiments
    Pros and Cons of Quasi-Experiments
    Observational Studies
    When to Use Observational Studies
    Accounting for Confounders in Observational Studies
    Vitamin Supplement Observational Study
Evaluating Experiments
    Hill’s Criteria of Causation
    Properties of Good Data
    Reliability
    Validity
    Data Validity
    Experimental Validity
    Internal Validity
    External Validity
    Relationship Between Internal & External Validity
    Checklist for Good Experiments
    Review
Wrapping Up and Your Next Steps
    Review of What You Learned in this Book
    Next Steps for Further Study
My Other Books
    Hypothesis Testing: An Intuitive Guide
    Regression Analysis: An Intuitive Guide
References
    Recommended Citation for This Book
About the Author