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📘 Statistics: Informed Decisions Using Data – 6th Edition (Sullivan) – Test Bank

Unlock the complete test bank for Statistics: Informed Decisions Using Data, 6th Edition by Michael Sullivan III (ISBN-10: 0135780276, ISBN-13: 9780135780275). This resource provides practice questions, exercises, and solutions ideal for students, instructors, and data enthusiasts looking to master descriptive statistics, probability, inferential methods, regression, and nonparametric analysis.

🟢 I. Getting the Information You Need

1️⃣ Data Collection

• Understanding types of data 🔢

• Sampling methods: random, stratified, cluster, convenience 🧩

• Designing surveys and experiments 📝

• Minimizing bias and errors ⚠️

This chapter helps learners collect reliable and accurate data, a crucial step in making informed statistical decisions.

🟡 II. Descriptive Statistics

2️⃣ Organizing and Summarizing Data

• Frequency tables, histograms, and bar charts 📊

• Stem-and-leaf plots & pie charts 🥧

• Data visualization best practices 👁️

3️⃣ Numerically Summarizing Data

• Measures of central tendency: mean, median, mode 🎯

• Measures of variability: range, variance, standard deviation 📏

• Interquartile range and percentiles 🔢

4️⃣ Describing the Relation Between Two Variables

• Scatterplots and correlation 🔵

• Covariance and strength of association 💪

• Basic linear regression 📐

These sections provide the foundation for analyzing patterns in data and preparing for advanced statistical inference.

🔵 III. Probability & Probability Distributions

5️⃣ Probability

• Basic probability rules 🎲

• Independent and dependent events 🔗

• Conditional probability and Bayes’ Theorem 📊

6️⃣ Discrete Probability Distributions

• Binomial and Poisson distributions ✅

• Expected value and standard deviation 📏

• Applications in real-life problems 🌐

7️⃣ The Normal Probability Distribution

• Bell-shaped curve properties 🔔

• Z-scores and standardization 📉

• Calculating probabilities under the normal curve ➕

Mastering probability helps students quantify uncertainty and make data-driven decisions.

🟣 IV. Inference: From Samples to Population

8️⃣ Sampling Distributions

• Distribution of sample means 📊

• Central Limit Theorem ⚡

• Variation of sample proportions 🔢

9️⃣ Estimating the Value of a Parameter

• Point and interval estimates 🎯

• Confidence intervals for means and proportions ✅

• Margin of error 📏

10️⃣ Hypothesis Tests Regarding a Parameter

• Steps for hypothesis testing 📝

• Significance levels and p-values 📉

• Type I and Type II errors ⚠️

11️⃣ Inference on Two Population Parameters

• Comparing two means or proportions 📊

• Paired and independent samples 🔗

12️⃣ Inference on Categorical Data

• Chi-square tests for independence and goodness-of-fit ✅

• Analyzing categorical relationships 🔵

13️⃣ Comparing Three or More Means

• One-way ANOVA and F-tests 📈

• Post-hoc comparisons 🔄

14️⃣ Inference on the Least-Squares Regression Model & Multiple Regression

• Regression coefficients and prediction 📐

• R² and model fit 💪

• Multiple regression applications 🔗

15️⃣ Nonparametric Statistics

• Rank-based tests 🏆

• Mann-Whitney, Kruskal-Wallis tests 🔢

• Applications when assumptions are not met ⚠️

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