Discovering Statistics and Data Plus Integrated Review leads students through the study of statistics with an introduction to data.

It pays homage to the technology-driven data explosion by helping students understand the context behind future statistical concepts to be learned. Students are introduced to what data is, how we measure it, where it comes from, how to visualize it, and what kinds of career opportunities involve its analysis and processing.

 

This integrated course enhances curriculum-level statistics with applicable review skills to shorten the prerequisite sequence without compromising competency. Target specific remediation needs for just-in-time supplementation of foundational concepts.

Table of Contents:

Chapter 0: Strategies for Academic Success

0.1	How to Read a Math Textbook
0.2	Tips for Success in a Math Course
0.3	Tips for Improving Math Test Scores
0.4	Practice, Patience, and Persistence!
0.5	Note Taking
0.6	Do I Need a Math Tutor?
0.7	Tips for Improving Your Memory
0.8	Overcoming Anxiety
0.9	Online Resources
0.10	Preparing for a Final Math Exam
0.11	Managing Your Time Effectively

Chapter 1.R: Integrated Review

1.R.1	Problem Solving with Whole Numbers
1.R.2	Introduction to Decimal Numbers
1.R.3	Exponents and Order of Operations

Chapter 1: Statistics and Problem Solving

1.1-1.8

Introduction to Statistical Thinking

Chapter 2.R: Integrated Review

2.R.1	Introduction to Fractions and Mixed Numbers
2.R.2	Decimal Numbers and Fractions
2.R.3	Decimals and Percents
2.R.4	Comparisons and Order of Operations with Fractions
2.R.5	Estimating and Order of Operations with Decimal Numbers
2.R.6	Fractions and Percents

Chapter 2: Data, Reality, and Problem Solving

2.1	The Lords of Data
2.2	Data Classification
2.3	Time Series Data vs. Cross-Sectional Data
Chapter 2 Review	Chapter 2 Review

Chapter 3.R: Integrated Review

3.R.1	Reading Graphs
3.R.2	Constructing Graphs from a Database
3.R.3	The Real Number Line and Absolute Value

Chapter 3: Visualizing Data

3.1	Frequency Distributions
3.2	Displaying Qualitative Data Graphically
3.3	Constructing Frequency Distributions for Quantitative Data
3.4	Histograms and Other Graphical Displays of Quantitative Data
3.5	Analyzing Graphs
Chapter 3 Review	Chapter 3 Review

Chapter 4.R: Integrated Review

4.R.1	Addition with Real Numbers
4.R.2	Subtraction with Real Numbers
4.R.3	Multiplication and Division with Real Numbers
4.R.4	Simplifying and Evaluating Algebraic Expressions
4.R.5	Evaluating Radicals

Chapter 4: Describing and Summarizing Data From One Variable

4.1	Measures of Location
4.2	Measures of Dispersion
4.3	Measures of Relative Position, Box Plots, and Outliers
4.4	Data Subsetting
4.5	Analyzing Grouped Data
4.6	Proportions and Percentages
Chapter 4 Review	Chapter 4 Review

Chapter 5.R: Integrated Review

5.R.1	The Cartesian Coordinate System
5.R.2	Graphing Linear Equations in Two Variables
5.R.3	Slope-Intercept Form
5.R.4	Point-Slope Form

Chapter 5: Discovering Relationships

5.1	Scatterplots and Correlation
5.2	Fitting a Linear Model
5.3	Evaluating the Fit of a Linear Model
5.4	Fitting a Linear Time Trend
5.5	Scatterplots for More Than Two Variables
Chapter 5 Review	Chapter 5 Review

Chapter 6.R: Integrated Review

6.R.1	Multiplication with Fractions
6.R.2	Division with Fractions
6.R.3	Least Common Multiple (LCM)
6.R.4	Addition and Subtraction with Fractions
6.R.5	Addition and Subtraction with Mixed Numbers
6.R.6	Union and Intersection of Sets

Chapter 6: Probability, Randomness, and Uncertainty

6.1	Introduction to Probability
6.2	Addition Rules for Probability
6.3	Multiplication Rules for Probability
6.4	Combinations and Permutations
6.5	Bayes Theorem
Chapter 6 Review	Chapter 6 Review

Chapter 7.R: Integrated Review

7.R.1	Order of Operations with Real Numbers
7.R.2	Solving Linear Inequalities in One Variable
7.R.3	Compound Inequalities

Chapter 7: Discrete Probability Distributions

7.1	Types of Random Variables
7.2	Discrete Random Variables
7.3	The Discrete Uniform Distribution
7.4	The Binomial Distribution
7.5	The Poisson Distribution
7.6	The Hypergeometric Distribution
Chapter 7 Review	Chapter 7 Review

Chapter 8.R: Integrated Review

8.R.1	Area
8.R.2	Solving Linear Equations: ax + b = c
8.R.3	Working with Formulas

Chapter 8: Continuous Probability Distributions

8.1	The Uniform Distribution
8.2	The Normal Distribution
8.3	The Standard Normal Distribution
8.4	Applications of the Normal Distribution
8.5	Assessing Normality
8.6	Approximation to the Binomial Distribution
Chapter 8 Review	Chapter 8 Review

Chapter 9: Samples and Sampling Distributions

9.1	Random Samples
9.2	Introduction to Sampling Distributions
9.3	The Distribution of the Sample Mean and the Central Limit Theorem
9.4	The Distribution of the Sample Proportion
9.5	Other Forms of Sampling
Chapter 9 Review	Chapter 9 Review

Chapter 10.R: Integrated Review

10.R.1	Absolute Value Equations
10.R.2	Absolute Value Inequalities

Chapter 10: Estimation: Single Samples

10.1	Point Estimation of the Population Mean
10.2	Interval Estimation of the Population Mean
10.3	Estimating the Population Proportion
10.4	Estimating the Population Standard Deviation or Variance
Chapter 10 Review	Chapter 10 Review

Chapter 11.R: Integrated Review

11.R.1	Translating English Phrases and Algebraic Expressions
11.R.2	Applications: Scientific Notation

Chapter 11: Hypothesis Testing: Single Samples

11.1	Introduction to Hypothesis Testing
11.2a	Testing a Hypothesis about a Population Mean with Sigma Known
11.2b	Testing a Hypothesis about a Population Mean with Sigma Unknown
11.2c	Testing a Hypothesis about a Population Mean using P-values
11.3	The Relationship Between Confidence Interval Estimation and Hypothesis Testing
11.4a	Testing a Hypothesis about a Population Proportion
11.4b	Testing a Hypothesis about a Population Proportion using P-values
11.5	Testing a Hypothesis about a Population Standard Deviation or Variance
11.6	Practical Significance vs. Statistical Significance
Chapter 11 Review	Chapter 11 Review

Chapter 12: Inferences about Two Samples

12.1a	Inference about Two Means: Independent Samples with Sigma Known
12.1b	Inference about Two Means: Independent Samples with Sigma Unknown
12.2	Inference about Two Means: Dependent Samples (Paired Difference)
12.3	Inference about Two Population Proportions
Chapter 12 Review	Chapter 12 Review

Chapter 13: Regression, Inference, and Model Building

13.1	Assumptions of the Simple Linear Model
13.2	Inference Concerning the Slope
13.3	Inference Concerning the Model’s Prediction
Chapter 13 Review	Chapter 13 Review

Chapter 14: Multiple Regression

14.1	The Multiple Regression Model
14.2	The Coefficient of Determination and Adjusted R-Squared
14.3	Interpreting the Coefficients of the Multiple Regression Model
14.4	Inference Concerning the Multiple Regression Model and Its Coefficients
14.5	Inference Concerning the Model’s Prediction
14.6	Multiple Regression Models with Qualitative Independent Variables
Chapter 14 Review	Chapter 14 Review

Chapter 15: Analysis of Variance (ANOVA)

15.1	One-Way ANOVA
15.2	Two-Way ANOVA: The Randomized Block Design
15.3	Two-Way ANOVA: The Factorial Design
Chapter 15 Review	Chapter 15 Review

Chapter 16: Looking for Relationships in Qualitative Data

16.1	The Chi-Square Distribution
16.2	The Chi-Square Test for Goodness of Fit
16.3	The Chi-Square Test for Association
Chapter 16 Review	Chapter 16 Review

Chapter 17: Nonparametric Tests

17.1	The Sign Test
17.2	The Wilcoxon Signed-Rank Test
17.3	The Wilcoxon Rank-Sum Test
17.4	The Rank Correlation Test
17.5	The Runs Test for Randomness
17.6	The Kruskal-Wallis Test
Chapter 17 Review	Chapter 17 Review

Appendix

A.1	Name that Distribution
A.2	Direct Mail
A.3	Type II Errors
A.4	Games of Chance
A.5	Comparing Two Population Variances
A.6	Statistical Process Control

 

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