Quantitative Investigations in the Biosciences Using MINITAB

Description

Content: Cover Half Title Title Page Copyright Page Contents Preface Chapter 1. Introduction 1.1 Introduction 1.2 The process of conducting an investigation The big question Problem types The hypothesis The data and choice of investigative method The analysis The conclusions and communication 1.3 Summary Part I: Data Familiarisation and Presentation Chapter 2. Exploring, Summarising, and Presenting Data 2.1 Introduction 2.2 Organising data using Minitab 2.3 Numerical methods of data description Listing and tabulating data Measures of central tendency Measures of spread. Minitab methods of numerical data description2.4 Graphical methods of data description Histograms, bar charts, and stem-and-leaf diagrams Box-and-whisker plots Graphs and scatter diagrams Pie charts 2.5 Exercises 2.6 Summary of Minitab commands 2.7 Summary Chapter 3. Reliability, Probability, and Confidence 3.1 Introduction 3.2 Reliability 3.3 Probability The binomial distribution and binomial probabilities The Poisson distribution and Poisson probabilities The normal distribution and normal probabilities 3.4 Confidence intervals Confidence interval of a mean. Confidence interval of a proportion3.5 Graphical presentation of reliability and confidence 3.6 Exercises 3.7 Summary of Minitab Commands 3.8 Summary Chapter 4. Sampling 4.1 Introduction 4.2 Sampling techniques Simple random sampling Stratified random sampling Systematic sampling 4.3 Sample size determination How large a sample is necessary when estimating a population mean? How large a sample is necessary when estimating a population proportion? 4. 4 Exercises 4.5 Summary of Minitab commands 4.6 Summary Part II: Questions of Comparison General Introduction. Chapter 5. Single Sample Comparisons5.1 Introduction 5.2 Comparisons of a large sample (or where the population standard deviation is known) 5.3 Comparisons of a small sample 5.4 Comparisons of samples that have not been drawn from normal distributions Comparing nominal data against a standard value Comparing measured data against a standard value 5.5 Exercises 5.6 Summary of Minitab commands 5.7 Summary Chapter 6. Comparing Two Samples 6.1 Introduction 6.2 Comparing two independent samples Comparing two sample means. Comparing two independent samples when normality cannot be assumed6.3 Comparison of two related (or paired) samples Comparison of paired samples when normality can be assumed Comparison of paired samples when normality cannot be assumed Paired sign test Wilcoxon matched-pairs signed-ranks test 6.4 Exercises 6.5 Summary of Minitab commands 6.6 Summary Chapter 7. Multiple Comparisons 7.1 Introduction 7.2 Comparisons involving many levels of a single factor Between-subject comparisons where normality can be assumed The Kruskal- Wallis non-parametric oneway ANOVA.