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Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries - Paperback | Diverse Reads

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

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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.

ISBN-13: 9781735431109

Media Type: Paperback

Publisher: James D. Frost

Publication Date: 08-14-2020

Pages: 256

Product Dimensions: 6.00(w) x 9.00(h) x 0.54(d)

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 his own statistics website and writes a regular column for the American Society of Quality's Statistics Digest. Find him online at www.statisticsbyjim.com

Table of Contents

The Importance of Statistics

Draw Valid Conclusions

Avoid Common Pitfalls

Make an Impact in Your Field

Protect Yourself with Statistics

Statistics versus Anecdotal Evidence

Data Types, Graphs, and Finding Relationships

Quantitative versus Qualitative Data

Continuous and Discrete Data

Qualitative Data: Categorical, Binary, and Ordinal

Skewed Distributions

Identifying Outliers

Multimodal Distributions

Comparing Distributions between Groups

Histograms and Sample Size

Boxplots vs. Individual Value Plots

Two -Way Contingency Tables

Summary Statistics and Relative Standing

Percentiles

Calculating Percentiles

Measures of Central Tendency

Measures of Variability

Correlation

Interpreting Correlation Coefficients

Probability Distributions

Discrete Probability Distributions

Binomial and Other Distributions for Binary Data

Modelling Flu Outcomes Over Decades

Continuous Probability Distributions

Normal Distribution in Depth

Parameters of the Normal Distribution

Properties of the Normal Distribution

The Empirical Rule

Standard Normal Distribution and Standard Scores

Calculating Z-scores

Using a Table of Z-scores

Descriptive and Inferential Statistics

Descriptive Statistics

Example of Descriptive Statistics

Inferential Statistics

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

Statistics in Scientific Studies

Research Your Study Area

Operationalize Your Study

Data Collection

Statistical Analysis

Writing the Results

Experimental Methods

Types of Variables in Experiments

Causation versus Correlation

Confounding Variables

True Randomized Experiments

Random Assignment

Flu Vaccination Experiment

Quasi-Experiments

Observational Studies

Accounting for Confounders in Observational Studies

Vitamin Supplement Observational Study

Evaluating Experiments

Hill's Criteria of Causation

Reliability

Validity

Data Validity

Experimental Validity

Internal Validity

External Validity

Checklist for Good Experiments