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

Cengage Cengage

WebAssign Instant Access for Statistics by Learning Objective, Single-Term
ISBN-13: 9781337687584
Copyright 2019 | Published
List Price: USD $103.00

STATISTICS BY LEARNING OBJECTIVE helps you master your statistics course by including in-question videos, easily-scannable narrative, a plethora of examples, and quick help tools in the homework. This course is specially designed in concert with dozens of students to efficiently help you learn statistics by providing you what you need, how you need it, when you need it. Learning objectives help you focus on what to learn at the moment. Each learning objective contains 6 examples, which are each major-specific, so you can see how statistics applies in your context.

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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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  • 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.

  • 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.

Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.

COMPOSE MODULE PARENT NRB STAT ISTICS LEARNING OBJECTIVE
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