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CHAPTER WISE BOOK SUMMARY
"Elementary Statistics," 14th Edition by Mario F. Triola, offers a comprehensive introduction to statistics, emphasizing real-world applications and data analysis. Below is a chapter-wise summary of the key topics covered in the textbook:
Chapter 1: Introduction to Statistics
1.1 Statistical and Critical Thinking: Introduces the importance of statistics and the role of critical thinking in analyzing data.
1.2 Types of Data: Discusses different data types, including qualitative and quantitative data.
1.3 Collecting Sample Data: Explores methods for collecting data samples and the significance of sampling techniques.
1.4 Ethics in Statistics: Addresses ethical considerations in statistical practice.
Chapter 2: Exploring Data with Tables and Graphs
2.1 Frequency Distributions for Organizing and Summarizing Data: Explains how to organize data using frequency distributions.
2.2 Histograms: Covers the creation and interpretation of histograms.
2.3 Graphs That Enlighten and Graphs That Deceive: Discusses effective and misleading graphical representations.
2.4 Scatterplots, Correlation, and Regression: Introduces scatterplots and the concepts of correlation and regression.
Chapter 3: Describing, Exploring, and Comparing
Data
3.1 Measures of Center: Focuses on measures such as mean, median, and mode.
3.2 Measures of Variation: Explores range, variance, and standard deviation.
3.3 Measures of Relative Standing and Boxplots: Introduces percentiles, quartiles, and boxplots.
Chapter 4: Probability
4.1 Basic Concepts of Probability: Covers foundational probability concepts.
4.2 Addition Rule and Multiplication Rule: Discusses rules for combining probabilities.
4.3 Complements, Conditional Probability, and Bayes' Theorem: Explores advanced probability topics.
4.4 Counting: Introduces counting techniques used in probability.
4.5 Simulations for Hypothesis Tests: Discusses using simulations in hypothesis testing.
Chapter 5: Discrete Probability Distributions
5.1 Probability Distributions: Explains discrete probability distributions.
5.2 Binomial Probability Distributions: Focuses on binomial distributions.
5.3 Poisson Probability Distributions: Introduces Poisson distributions.
Chapter 6: Normal Probability Distributions
6.1 The Standard Normal Distribution: Discusses properties of the standard normal distribution.
6.2 Real Applications of Normal Distributions: Applies normal distributions to real-world scenarios.
6.3 Sampling Distributions and Estimators: Explores sampling distributions and estimation.
6.4 The Central Limit Theorem: Introduces the central limit theorem.
6.5 Assessing Normality: Discusses methods for assessing normality in data.
6.6 Normal as Approximation to Binomial: Explains using normal distribution to approximate binomial probabilities.
Chapter 7: Estimating Parameters and Determining Sample Sizes
7.1 Estimating a Population Proportion: Covers estimation techniques for population proportions.
7.2 Estimating a Population Mean: Focuses on estimating population means.
7.3 Estimating a Population Standard Deviation or Variance: Discusses estimation of variability measures.
7.4 Bootstrapping: Using Technology for Estimates: Introduces bootstrapping methods for estimation.
Chapter 8: Hypothesis Testing
8.1 Basics of Hypothesis Testing: Introduces the framework of hypothesis testing.
8.2 Testing a Claim About a Proportion: Covers hypothesis tests for proportions.
8.3 Testing a Claim About a Mean: Discusses hypothesis tests for means.
8.4 Testing a Claim About a Standard Deviation or Variance: Explores tests for variability measures.
8.5 Resampling: Using Technology for Hypothesis Testing: Introduces resampling techniques in hypothesis testing.
Chapter 9: Inferences from Two Samples
9.1 Two Proportions: Discusses inference methods for comparing two proportions.
9.2 Two Means: Independent Samples: Covers inference techniques for independent sample means.
9.3 Matched Pairs: Explores analysis of matched pairs data.
9.4 Two Variances or Standard Deviations: Introduces methods for comparing variances.
9.5 Resampling: Using Technology for Inferences: Discusses resampling methods for inference.
Chapter 10: Correlation and Regression
10.1 Correlation: Explores the concept of correlation between variables.
10.2 Regression: Introduces regression analysis techniques.
10.3 Prediction Intervals and Variation: Discusses prediction intervals and variation in regression.
10.4 Multiple Regression: Covers multiple regression analysis.
10.5 Nonlinear Regression: Introduces nonlinear regression methods.
Get complete eBook Instant Download Link below
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(SPECIAL NOTE)
"We have all the books, eBooks, test banks, and solution manuals available at a cheap price for instant download. If you need any book other than this, feel free to contact us for instant access and downloads, please contact us via email or WhatsApp.
Whatsapp link: https://wa.me/+447507735190
Email: etutorsource@gmail.com
("And we also provide academic writing services.")
Do you need the best quality, organic,and plagiarismfree assignments, and dissertation help without using AI tools? I am a UK-based professional researcher and tutor. I have been consulting and tutoring for more than 14 years in dissertations, essay help, reports, and other assignments.
We are accepting a variety of projects. Some of the projects we have engaged in the past but not limited to; - Assignments
- Essay help
- Report
- Dissertation consulting
- Research proposal
- Literature review
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- Annotated bibliography
- PowerPoint presentation and oral script
- Proofreading and editing work
- Statistical Analysis Help & Tutoring Services (SPSS, Stata, R, EViews)
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Email: etutorsource@gmail.com
CHAPTER WISE BOOK SUMMARY