Statistics for Absolute Beginners (Second Edition)

by Oliver Theobald

Data is collected how far we travel, who we interact with online and where we spend our money. Every bit of data has a story to tell but isolated, these morsels of information lie dormant and useless, like unattached Lego blocks.

Written by the author of Amazon Best Seller Machine Learning for Absolute Beginners , this book guides you through the fundamentals of inferential and descriptive statistics with a mix of practical demonstrations, visual examples, historical origins, and plain English explanations. As a resource for beginners, this book won't teach you how to beat the market or predict the next U.S. election but ensures a concise and simple-to-understand supplement to a standard textbook.

This includes an introduction to important techniques used to infer predictions from data, such as hypothesis testing, linear regression analysis, confidence intervals, probability theory, and data distribution. Descriptive statistics techniques such as central tendency measures and standard deviation are also covered in this book.

Full Overview of Book Themes
• The Historical Development of Statistics
• Data Sampling
• Central Tendency Measures
• Measures Of Spread
• Measures Of Position
• Designing Hypothesis Tests
• Probability and Bayes Theory
• Regression Analysis
• Clustering Analysis

As the launchpad to quantitative research, business optimization or a promising career in data science, it's never been a better time to brush up on statistics or learn these concepts for the very first time.

157 pages, Hardcover

Published October 8, 2021

Reviews

[Srinivasan Nanduri · Rating 2 out of 5]

"**Statistics for Absolute Beginners**" is designed to offer an accessible introduction to statistics, catering to those who have little to no background in the subject. The book covers fundamental statistical concepts, techniques, and applications, helping readers grasp the basics through simple explanations, visual aids, and practical examples.

### **Key Takeaways**

1. **Understanding Descriptive Statistics**:
- Key concepts such as mean, median, mode, range, variance, and standard deviation
- Learn to summarize and describe datasets using measures of central tendency and dispersion.

2. **Probability**:
- Basics of probability theory, including definitions of probability, types of events, and probability rules, are introduced.
- Differentiate between dependent and independent events, and how to calculate simple probabilities.

3. **Distributions**:
- Provides an understanding of probability distributions (normal, binomial, and others), and how they model real-world data.
- Key properties of the normal distribution and the importance of the bell curve are highlighted.

4. **Hypothesis Testing**:
- Readers learn the steps involved in hypothesis testing, including formulating null and alternative hypotheses, selecting significance levels, and interpreting results.
- Common tests like t-tests and chi-square tests

5. **Correlation and Regression**:
- Explains the concepts of correlation (relationship between two variables) and regression (predicting one variable based on another).
- Calculate and interpret correlation coefficients and perform simple linear regression.

6. **Data Collection and Sampling**:
- Discusses different methods of data collection (surveys, experiments, observational studies) and types of sampling (random, stratified, etc.).
- Emphasizes the importance of good data collection practices for accurate statistical analysis.

7. **Practical Applications**:
- Discusses how statistics is used in various fields like business, healthcare, and social sciences.

8. **Visual Representation of Data**:
- Importance of charts, graphs, and tables in understanding and presenting data effectively.
- How to construct and interpret histograms, pie charts, bar graphs, and scatter plots.

[Qori Ilmanudin · Rating 4 out of 5]

This book is a good introduction to getting familiar with statistics. It covers basic concepts from 0 to n. You’ll still need to learn some fundamentals elsewhere, as it doesn’t cover everything.

I liked the example where the author tested the truthfulness of a real-life event. The downside of this book is that it could offer a simpler way to "give" or explain things—especially since the cover says it's for "absolute beginners."

[Alessandra · Rating 1 out of 5]

I read 44% of the book & learned maybe 2 things. Majority of it is just the history of statistics. I didn’t finish the book. There’s some examples but a lot of it is history throughout each chapter. I’ll probably stick to YouTube for help on statistics instead of reading this or at least trying to

[Mick · Rating 5 out of 5]

data is fun