WebAssign Instant Access for Statistics by Learning Objective, Single-Term, 1st Edition

Cengage

Copyright 2019
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WebAssign Instant Access for Statistics by Learning Objective, Single-Term 1st Edition by Cengage

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Overview

STATISTICS BY LEARNING OBJECTIVE enables you to teach what you want to teach, how you want to teach, when you want to teach it. With a comprehensive list of Intro Stats topics organized by learning objective, modeling each learning objective to be as standalone as possible, and written in a blog-like fashion, STATISTICS BY LEARNING OBJECTIVE melds itself to your preferred method of teaching, while empowering the student to learn through videos, examples, and practice. \n \nEach learning objective contains at least 6 examples, which are each major-specific, so your students can see how statistics applies in their context. Also included are 10 homework questions per learning objective, spanning from recall questions to critical thinking and application open response. The WebAssign course contains 2000+ questions, labs, projects, test banks, concept questions, Watch Its, and Master Its.\n\nNEW for Fall 2020 - Turn your students into statistical thinkers with the Statistical Analysis and Learning Tool (SALT). SALT is an easy-to-use data analysis tool created with the intro-level student in mind. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data. SALT is built by Cengage, comes integrated in Cengage WebAssign Statistics courses and available to use standalone.

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NOTE: This title is also available in WebAssign with Corequisite Support that provides the flexibility to match any corequisite implementation model and empowers you to deliver high quality content at the right time for your students at an affordable price.
NEW for Fall 2020 - Turn your students into statistical thinkers with the Statistical Analysis and Learning Tool (SALT). SALT is an easy-to-use data analysis tool created with the intro-level student in mind. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data. SALT is built by Cengage, comes integrated in Cengage WebAssign Statistics courses and available to use standalone.

Features

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Organized by learning objective, each learning objective contains 6 examples that use a different major-specific context to show students how statistics applies in their context.
Master It Tutorials break big problems down into smaller, more manageable steps to help students get to the root of the question.
Watch It solution videos for a subset of quantitative problems. One algorithmic version of each problem having a Watch It video is shown.
Stats in Practice videos from the news introduce each chapter so that students can understand real-world context of what they’re learning and stay engaged.
Using the JMP interactive applet embedded within WebAssign, students can interact with visualizations of real data.
Pre-made Labs make it easier for students to apply their knowledge.
Project Milestones allow one place to ideate, collaborate, and submit a longer-term project.
Concept questions provide a new way of engaging with non-computational questions. Students enter a free response before they choose a multiple-choice answer, which helps students be better prepared for tests.
Test banks provide a pool of assessments for use in quizzes, tests, and exams.
STATISTICS BY LEARNING OBJECTIVE is written in a blog-like fashion for easy readability, scanning, and understandability.

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1. Concepts of Statistics.
Branches of Statistics. Population and Sample. Variable Types. Parameter Versus Statistic. Types of Data.
2. Experiments and Types of Studies.
Types of Studies. Experiment. Experimental Design.
3. Sampling Methods.
Simple Random Sample. Stratified Sampling. Systematic Sampling. Convenience Sampling. Bias.
4. Numerical Measures.
Central Tendency. Relative Location. Variation.
5. Tabular Representations.
Summarizing Data with Tables.
6.Graphical Representations.
Descriptions of Distributions. Graphical Representations for Categorical Data. Graphical Representations for Numerical Data.
7. Concepts of Probability.
Defining Probability and Probabilities of Events.
8. Conditional Probability.
Determining Conditional Probability of Events.
9. Counting.
Using Techniques of Counting.
10. Discrete Probability Distributions and Binomial Distribution.
Discrete Random Variables. Binomial Distribution.
11. More Discrete Probability Distributions.
Geometric Distribution. Hypergeometric Distribution. Poisson Distribution. Multinomial Distribution.
12. Continuous Probability Distribution and Normal Distribution.
Continuous Random Variables. Normal Distribution.
13. More Continuous Probability Distributions.
Student's t Distribution. Chi-Square Distribution. F Distribution. Uniform Probability Distribution.
14. Sampling Distributions.
Sampling Distribution of the Sample Mean. Sampling Distribution of Sample Proportion. Sampling Distributions for Two Samples. Sampling Distributions for Two Samples. Sampling Distributions for Two Samples.
15. Estimation for One Sample.
Estimating One Mean. Estimating One Proportion. Estimating One Variance.
16. Estimation for Two Samples.
Estimating Two Means - Independent Samples. Estimating Two Means - Paired Samples. Estimating Two Proportions.
17. Hypothesis Tests for One Sample.
Testing One Mean. Testing One Proportion. Testing One Variance.
18. Hypothesis Tests for Two Samples.
Testing Two Means - Independent Samples. Testing Two Means - Paired Samples. Testing Two Proportions. Testing Two Variances.
19. Chi-Square Tests.
Goodness-of-Fit Test. Test of Homogeneity. Test of Independence.
20. Correlation and Regression.
Summarizing Bivariate Data. Correlation. Simple Linear Regression.
21. Multiple Regression.
Multiple Linear Regression Model.
22. One-Way Analysis of Variance.
Testing Two or More Means – Independent Samples.
23. Two-Way Analysis of Variance.
Testing Two or More Means – Two Factors or Treatments.
24. Nonparametric Methods.
Sign Test. Wilcoxon Rank Sum Test. Spearman Rank Correlation. Kruskal-Wallis Test. McNemar's Test.

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