Choosing and Using Statistics

Preface. 1 Eight steps to successful data analysis. 2 The basics. Observations. Hypothesis testing. P-values. Sampling. Experiments. Statistics. 3 Choosing a test: a key. Remember: eight steps to successful data analysis. The art of choosing a test. A key to assist in your choice of statistical test. 4 Hypothesis testing, sampling and experimental design. Hypothesis testing. Acceptable errors. P-values. Sampling. Experimental design. 5 Statistics, variables and distributions. What are statistics? Types of statistics. What is a variable? Types of variables or scales of measurement. Types of distribution. Discrete distributions. Continuous distributions. Non-parametric 'distributions'. 6 Descriptive and presentational techniques. General advice. Displaying data: summarizing a single variable. Displaying data: showing the distribution of a single variable. Descriptive statistics. Using the computer packages. Displaying data: summarizing two or more variables. Displaying data: comparing two variables. Displaying data: comparing more than two variables. 7 The tests 1: tests to look at differences. Do frequency distributions differ? Do the observations from two groups differ? Do the observations from more than two groups differ? There are two independent ways of classifying the data. More than one observation for each factor combination (with replication). There are more than two independent ways to classify the data. Not all classifications are independent. Nested or hierarchical designs. 8 The tests 2: tests to look at relationships. Is there a correlation or association between two variables? Is there a cause-and-effect relationship between two variables? Tests for more than two variables. 9 The tests 3: tests for data exploration. Types of data. Observation, inspection and plotting. Symbols and letters used in statistics. Greek letters. Symbols. Upper-case letters. Lower-case letters. Glossary. Assumptions of the tests. Hints and tips. A table of statistical tests. Index.