Statistics 101 : from data analysis and predictive modeling to measuring distribution and determining probability, your essential guide to statistics / David Borman.

A crash course in statistics"--Cover.

Includes index.

The basics of statistics
How statistics are used
Key points of statistical analytics
Mixing up the test
Knowing the quality of your data
Modeling risk, measuring samples, and predicting
Frequency distributions
Dot plots, bar charts, histograms, frequency polygons
More ways to see numbers-based data
The mean, the median, and the mode
The range and interquartile range
Mean deviations and variations
The law of large numbers
Empirical probability and subjective probability
Yes or no
Basics of probability distributions
Analyzing probability distributions
The roll of the dice
Normal distribution
The central limit theorem
Outliers on the bell curve
Limited and unlimited data
Variance as a measure of risk
Size matters
Measuring distribution
What are confidence intervals?
Measuring confidence intervals
The basics of hypothesis testing
Taking it to the next level
Measuring large sample population proportions
The hypothesis test
Patterns in data
Predicting the future
The T-distribution
Groups of data
Tests for two populations
Statistics in academic research
Getting good data
A regression example
What regression data tables tell us
Determining the causes
Chi-square distribution
Anova basics
Anova at work
Quantitative research design
Quality of the data
Quantity and sourcing of the data
Appropriate survey design
The ethics of statistics
Big data, supercomputers, and artificial intelligence

From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you'll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun.-- Provided by publisher.