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"Essential Statistics," 3rd Edition by William Navidi and Barry Monk, is designed for introductory statistics courses, requiring only basic algebra as a prerequisite. The authors aim to present statistical concepts clearly and engagingly, ensuring both the mechanics and underlying principles are accessible to students. The textbook is structured into several chapters, each focusing on fundamental aspects of statistics:
1. Basic Ideas: Introduces foundational concepts in statistics, including sampling methods, types of data, experimental design, and potential biases in studies.
2. Graphical Summaries of Data: Covers techniques for visually representing data, such as bar graphs, histograms, and pie charts, and discusses how graphical representations can be misleading.
3. Numerical Summaries of Data: Focuses on descriptive statistics, including measures of central tendency (mean, median, mode), measures of variability (range, variance, standard deviation), and data positioning.
4. Probability: Explores the fundamentals of probability, including basic concepts, addition and multiplication rules, conditional probability, and counting principles.
5. Discrete Probability Distributions: Discusses random variables, particularly discrete ones, and delves into specific distributions like binomial and Poisson distributions.
6. The Normal Distribution: Examines the properties of the normal distribution, applications, sampling distributions, the Central Limit Theorem, and assessing normality in data.
7. Confidence Intervals: Introduces the concept of estimating population parameters using confidence intervals for means, proportions, and standard deviations.
8. Hypothesis Testing: Covers the principles and procedures of hypothesis testing for population means, proportions, and standard deviations, including discussions on test power.
9. Inferences on Two Samples: Focuses on comparing two populations through confidence intervals and hypothesis tests for differences in means, proportions, and variances, using both independent and paired samples.
10. Tests with Qualitative Data: Introduces chi-square tests for goodness-of-fit, independence, and homogeneity, applicable to categorical data analysis.
11. Correlation and Regression: Explores the relationship between variables using correlation coefficients and simple linear regression analysis, including inference on regression parameters. Each chapter is designed to build upon the previous ones, providing a comprehensive understanding of statistical methods and their applications. The authors emphasize clarity and accuracy, making the material suitable for students new to statistics.
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ise-essential-statistics-3rd-edition-by-william-navidibarry-monk