# Integrate Developmental Math with Statistics in Corequisite Course 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.

### 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 0.1 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

Interested in exploring this course?