SAMPLER - Pearson · 2020-06-03 · textbook or loose-leaf edition, which is an unbound, three-hole-punched version of the textbook that fits into a binder. Students can keep only

MyLab Statistics with Integrated Review

Introductory Statistics 3e ©2020 Robert Gould, Rebecca Wong, & Colleen Ryan

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Integrated Review in the MyLab for Gould’s Introductory Statistics can be used to

bring underprepared students up to speed, or simply to help students with a quick

refresher of previous topics. It can also be used in corequisite models.

Integrated Review provides developmental math content through a statistical lens by

rewriting text, exercises, and examples with a statistical focus and adding new topics

to properly prepare students for their first statistics course. Assignments for the

integrated review content are pre-built in MyLab Statistics, making them easy to

assign in your course!

Are your statistics students underprepared on prerequisite topics in your course?

You can set it all up in just 2 steps!

1 Create your Gould MyLab Statistics course

2 Choose your Print Options - Introductory Statistics textbook - Integrated Review Worksheets

Gould • Wong • Ryan MyLab Statistics with Integrated Review

Introductory Statistics, 3e ©2020



STEP 1 Create your course and assign the Integrated Review Assignments

Premade, editable Integrated

Review assignments are available

to assign in the Assignment

Manager. Integrated Review

landing pages (shown below) are

visible by default at the start of

most chapters, providing objective-

level review on prerequisite topics.

How does Integrated Review work?

1. Once you’ve assigned the

Integrated Review assignments,

students begin each chapter by

completing a Skills Check

assignment to pinpoint which

prerequisite skills topics, if any, they

need to review.

2. A personalized review

homework assignment helps

students remediate for any gaps in

skills identified by the Skills Check.

Each student receives just the help

he or she needs.

3. Additional review materials

(worksheets and videos) are available to

help students remediate on objectives

where they have gaps.

These materials are also linked as

learning aids for the exercises in the

personalized review homework, to focus

students’ attention on the resources they

need, when they need them.





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STEP 2 Print Options

You can package the textbook and/or the Integrated Review Worksheets with the MyLab Statistics access kit.

Introductory Statistics teaches students how to explore

and analyze real data to answer real-world problems.

Crafted by authors who are active in the classroom and

statistics education community, the 3rd edition pairs a

clear, conversational writing style with new and

frequent opportunities to apply statistical thinking. Its

tone and learning aids are designed to equip any

student to analyze, interpret, and tell a story about

modern data, regardless of the student’s mathematical

proficiency.

Introductory Statistics is available as a traditional

textbook or loose-leaf edition, which is an unbound,

three-hole-punched version of the textbook that fits

into a binder. Students can keep only the pages they

need and incorporate their notes.

The Integrated Review Worksheets for Introductory Statistics

provide additional practice for both the core course and

prerequisite content. The worksheets guide students

through the Integrated Review in MyLab Statistics by

objective and offers additional practice exercises with ample

space for students to show their work.

The Integrated Review Worksheets are available as PDF

files for download in MyLab Statistics, or can be

packaged with a MyLab Statistics access code or text.

Contact your Pearson Sales Representative for package options and more details. www.pearson.com/us/higher-education



http://www.pearson.com/us/higher-education

Integrated Review Topics

Evaluate squares

Apply square roots

Apply the order of operations

Evaluate expressions and formulas

Apply summation notation



Table of Contents

1.1 What Are Data?

1.2 Classifying and Storing Data

1.3 Investigating Data

1.4 Organizing Categorical Data

1.5 Collecting Data to Understand Causality

2.1 Visualizing Variation in Numerical Data

2.2 Summarizing Important Features of a

Numerical Distribution

2.3 Visualizing Variation in Categorical Variables

2.4 Summarizing Categorical Distributions

2.5 Interpreting Graphs

3.1 Summaries for Symmetric Distributions

3.2 What’s Unusual? The Empirical Rule and z-

scores

3.3 Summaries for Skewed Distributions

3.4 Comparing Measures of Center

3.5 Using Boxplots for Displaying Summaries

Chapter 1 Introduction to Data

Chapter 2 Picturing Variation with Graphs

Chapter 3 Numerical Summaries of Center and Variation

Chapter 4 Regression Analysis: Exploring Associations between Variables


Plot points

Review the skills for graphing

Find and interpret slope

Find the y-intercept of a line

Find values from a linear equation or graph

Graph a linear equation

Find and interpret a linear model

4.1 Visualizing Variability with a Scatterplot

4.2 Measuring Strength of Association with

Correlation

4.3 Modeling Linear Trends

4.4 Evaluating the Linear Model


Position values on a number line

Tally values

Find proportion


Identify variables in context

Classify data as a type of number

Round decimals

Convert between decimals, fractions, and

percents

Calculate relative frequencies

Find the percentage of a number


Chapter 5 Modeling Variation with Probability


Evaluate exponents

Write a fraction in lowest terms

Apply operations to fractions

Apply operations to decimals

Determine the intersection, union, and

complement of two sets

5.1 What is Randomness?

5.2 Finding Theoretical Probabilities

5.3 Associations in Categorical Variables

5.4 Finding Empirical and Simulated Probabilities

Chapter 6 Modeling Random Events: The Normal and Binomial Models


Find area

Interpret inequality notation

Evaluate formulas for normal probability

distributions

Evaluate formulas for binomial distributions

6.1 Probability Distributions Are Models of

Random Experiments

6.2 The Normal Model

6.3 The Binomial Model

Chapter 7 Survey Sampling and Inference


Find the middle value for an interval given in

either interval notation or as an equality

Find the distance from the middle value of an

interval to its endpoints

Write and interpret three different forms of

intervals (as used for confidence intervals)

Evaluate formulas used for confidence intervals

for proportions


for the difference of two proportions

7.1 Learning about the World through Surveys

7.2 Measuring the Quality of a Survey

7.3 The Central Limit Theorem for Sample

Proportions

7.4 Estimating the Population Proportion with

Confidence Intervals

7.5 Comparing Two Population Proportions with

Confidence

Chapter 8 Hypothesis Testing for Population Proportions


Evaluate formulas for hypothesis testing for

proportions

Evaluate formulas for two-sample hypothesis

testing for proportions

8.1 The Essential Ingredients of Hypothesis

Testing

8.2 Hypothesis Testing in Four Steps

8.3 Hypothesis Tests in Detail

8.4 Comparing Proportions from Two

Populations


Chapter 9 Inferring Population Means



for means


means


for comparing two population means


comparing two population means

9.1 Sample Means of Random Samples

9.2 The Central Limit Theorem for Sample

Means

9.3 Answering Questions about the Mean of a

Population

9.4 Hypothesis Testing for Means

9.5 Comparing Two Population Means

9.6 Overview of Analyzing Means

Chapter 10 Associations between Categorical Variables

10.1 The Basic Ingredients for Testing with

Categorical Variables

10.2 The Chi-Square Test for Goodness of Fit

10.3 Chi-Square Tests for Associations between

Categorical Variables

10.4 Hypothesis Tests When Sample Sizes Are

Small

Chapter 11 Multiple Comparisons and Analysis of Variance

11.1 Multiple Comparisons

11.2 The Analysis of Variance

11.3 The ANOVA Test

11.4 Post Hoc Procedures

Chapter 12 Experimental Design: Controlling Variation

12.1 Variation Out of Control

12.2 Controlling Variation in Surveys

12.3 Reading Research Papers


Evaluating formulas for testing with categorical

variables

Chapter 13 Inference without Normality

Chapter 14 Inference for Regression

13.1 Transforming Data

13.2 The Sign Test for Paired Data

13.3 Mann-Whitney Test for Two Independent

Groups

13.4 Randomization Tests

14.1 The Linear Regression Model

14.2 Using the Linear Model

14.3 Predicting Values and Estimating Means

Documents

SAMPLER - Pearson · 2020-06-03 · textbook or loose-leaf edition, which is an unbound, three-hole-punched version of the textbook that fits into a binder. Students can keep only