Essential Statistics 2025 Evergreen Release By William Navidi
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Essential Statistics 2025 Evergreen Release By William Navidi

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729
File size
24.54 MB
Format
Digital PDF
Category
eBook[PDF]
About this ebook
Essential Statistics: 2025 Evergreen Release by William Navidi and Barry Monk is a comprehensive textbook structured across 11 core chapters. It covers foundational concepts, data visualization, descriptive metrics, probability theory, and both univariate and bivariate inferential methodologies. [1, 2, 3]
📋 Complete Chapter Breakdown
The content spans the following main topics and sequence: [1]
  • Chapter 1: Basic Ideas
    • Sampling methods and types of data
    • Designing experimental and observational studies [1, 2]
  • Chapter 2: Graphical Summaries of Data
    • Frequency distributions and contingency tables
    • Histograms, bar charts, dot plots, stem-and-leaf plots, and pie charts
    • Identifying misleading or biased graphical representations [1, 2, 3, 4]
  • Chapter 3: Numerical Summaries of Data
    • Measures of center (mean, median, mode)
    • Measures of spread (variance, standard deviation, percentiles, IQR)
    • Box plots and outlier detection [1, 2, 3]
  • Chapter 4: Probability
    • Basic rules, addition, multiplication, and conditional probability
    • Independence and tree diagrams
    • Counting principles and permutations/combinations [1, 2, 3]
  • Chapter 5: Discrete Probability Distributions
    • Random variables and expected value calculations
    • The Binomial distribution [1, 2]
  • Chapter 6: The Normal Distribution
    • Standard normal curve and z-scores
    • Central Limit Theorem and sampling distributions
    • Assessing normality in data subsets [1, 2, 3]
  • Chapter 7: Confidence Intervals
    • Estimating a population mean (z and t distributions)
    • Estimating a population proportion [1, 2, 3]
  • Chapter 8: Hypothesis Testing
    • One-sample tests for means and proportions
    • P-values, significance levels (α), and test power [1, 2, 3, 4]
  • Chapter 9: Inferences on Two Samples
    • Comparing two independent population means
    • Matched pairs / dependent sampling
    • Comparing two independent population proportions [1, 2, 3]
  • Chapter 10: Tests with Qualitative Data
    • Chi-Square Goodness-of-Fit tests
    • Chi-Square tests for independence and homogeneity [1, 2]
  • Chapter 11: Correlation and Regression
    • Scatter plots and the correlation coefficient (r)
    • Simple linear regression equations and the least-squares line
    • Inference on regression parameters and predictions [1, 2, 3]
💡 Notable Pedagogical Themes
  • Algebra-Based: The only mathematical prerequisite is basic algebra, making the mechanics accessible. [1, 2]
  • Technology Integration: The book weaves step-by-step instructions and software screenshots for the TI-84 Plus Graphing Calculator, Microsoft Excel, and Minitab throughout the chapters. [1, 2]
  • Real-World Contexts: Exercises lean heavily into contemporary datasets spanning health sciences, social sciences, economics, and pop culture. [1, 2]

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Topics

Assessing normality in data subsets Central Limit Theorem and sampling distributions Chi-Square tests for independence and homogeneity Comparing two independent population proportions Confidence Intervals Estimating a population mean (z and t distributions) contemporary datasets spanning health sciences social sciences economics and pop culture Correlation and Regression Scatter plots and the correlation coefficient (r) Counting principles and permutations/combinations Designing experimental and observational studies Discrete probability distributions Graphical Summaries of Data Frequency distributions and contingency tables Histograms bar charts dot plots stem-and-leaf plots and pie charts Hypothesis Testing One-sample tests for means and proportions. P-values significance levels (α) and test power Identifying misleading or biased graphical representations Independence and tree diagrams Inference on regression parameters and predictions Inferences on Two Samples Comparing two independent population means Matched pairs / dependent sampling Measures of spread (variance standard deviation percentiles IQR) Numerical Summaries of Data Measures of center (mean median mode) Probability Basic rules addition multiplication and conditional probability Random variables and expected value calculations Sampling methods and types of data Simple linear regression equations and the least-squares line Tests with Qualitative Data: Chi-Square goodness-of-fit tests The Binomial distribution The Normal Distribution Standard normal curve and z-scores TI-84 Plus Graphing Calculator Microsoft Excel and Minitab
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