24056 Shanker

M&IS 24056:Fundamentals of Business Statistics

Summer 2014

Table of Contents

Course Description

This course is an introduction to concepts in statistical methods and their applications to real-world problems. This course will examine both the theoretical and practical side of the different methods. Students will be given ample opportunities to apply the techniques to different problems. The goal of the course is for students to understand fundamental statistical concepts and methods, and their applications.

Course Requirements

Last day to withdraw from a course:  Sunday, June 29, 2014.

Prerequisites: Math 11011 (Algebra).  Students attending the course who do not have the proper prerequisite risk being deregistered from the class.

Enrollment: Students have responsibility to ensure they are properly enrolled in classes.  You are advised to review your official class schedule (using Student Tools on FlashLine) during the first two weeks of the semester to ensure you are properly enrolled in this class and section.  Should you find an error in your class schedule, you have until Thursday, June 12, 2014 to correct the error.  If registration errors are not corrected by this date and you continue to attend and participate in classes for which you are not officially enrolled, you are advised now that you will not receive a grade at the conclusion of the semester for any class in which you are not properly registered.

Students With Disabilities: University policy 3342-3-01.3 requires that students with disabilities be provided reasonable accommodations to ensure their equal access to course content. If you have a documented disability and require accommodations, please contact the instructor at the beginning of the semester to make arrangements for necessary classroom adjustments. Please note, you must first verify your eligibility for these through Student Accessibility Services (contact 330-672-3391 or visit http://www.kent.edu/sas/index.cfm for more information on registration procedures).

Academic Honesty: Cheating means to misrepresent the source, nature, or other conditions of your academic work (e.g., tests, papers, projects, assignments) so as to get undeserved credit. In addition, it is considered cheating when one cooperates with someone else in any such misrepresentation. The use of the intellectual property of others without giving them appropriate credit is a serious academic offense. It is the University's policy that cheating or plagiarism result in receiving a failing grade for the work or course. Repeat offenses result in dismissal from the University.

Unless noted, all assessments are open-book, open notes, but please remember that academic dishonesty will result in a failing grade, and may result in dismissal from the University. As part of the instructor tools, I can observe the progress of each student, and also of the class. As such, it is within my right to ask any student suspected of cheating to establish the validity of their work. Failure to do so will result in failing grade.

Course Materials

All class materials can be accessed directly at StatsPortal (http://courses.bfwpub.com/ips7e.php). A link to the StatsPortal can also be found at Blackboard Learn (http://learn.kent.edu). We will be using the StatsPortal for all our coursework. You do not need any other materials.

The following steps provide the most economical way to gain access to the StatsPortal:

1. Go to http://courses.bfwpub.com/ips7e.php
2. Click on Purchase (on the right side of the screen)
3. A new window will pop up. Select OH for the drop down prompt “Select the state or province where your institution is located:”
4. Next, select Kent State University for “Select your institution:”
5. Finally, select our course.
6. When you register at the StatsPortal, it is important that you use your Kent Email address, and your name exactly as given in your student records. But, choose a password different from your Flashline password.

The cost for online access is $85.99. Please note that the StatsPortal includes the eBook (see below) – therefore you do not need to acquire both the portal and the textbook, but if you prefer a printed text, StatsPortal can be purchased with the text for an additional fee.

Course Structure and Navigation

StatsPortal is a complete online learning solution containing an eBook, study Resources (such as tutorials, chapter quizzes, solutions, interactive applets, etc.), and  Assignments. For our course, you have access to the following materials:

eBook: A complete multimedia textbook with the ability to highlight and take notes. The eBook duplicates the textbook Introduction to the Practice of Statistics, Seventh Edition, Moore, McCabe, and Craig, W.H. Freeman and Company. Embedded within the eBook are the following:

• StatTutor: Tutorials that explain statistics.
• Applets: These let you interactively explore different statistical concepts.
• Datasets: These provide you with the data for the examples and exercises in the book.
• Crunchit!: This is the statistical software built into the book.

Resources: Here, you have access to the following:

• StatClips Videos: These are video lectures produced by the publisher.
• Stat @ Work Videos: These videos show the practical application of statistics.
• Technology Manuals: Help manuals for different statistical software
• Tables: Statistical tables

Assignments: Assessments assigned by your instructor. These include:

• Pre-Test and Post-Test: These quizzes allow you to create a personalized study plan. Always take the Pre-Test before you start the chapter, and the Post-Test after you have studied the chapter. You will then be provided with a personalized study plan. These quizzes are not graded, and can be taken multiple times.
• Learning Curve: This is a formative assessment activity that uses a game-like interface to guide you through a series of questions catered to your individual level of understanding. Along the way, and after you complete the activity, you will be directed to specific resources that help you learn. This activity is graded, and you receive points by reaching a Target Score for each activity. Activities are graded on a pass/fail basis. Every student who completes the activity receives a grade of 100%. Students who start but don't complete the activity remain at 0%. You can find the complete FAQ under each activity.
• Quizzes and Examinations: These assessments are graded. You should only take these assessments once you are satisfied you know the material. More information on graded assessments are detailed later in the syllabus.

To help you navigate and access the materials in a manner conducive to learning, I have created Lesson Plans. These lesson plans contain selected materials from the eBook, Resources, and Assignments, and instructor developed audio lectures, organized as follows:

• Read, Listen, and Practice: This section contains all materials needed for you to learn and practice your knowledge. They include the pre-test, audio lectures, selected video clips, and sections from the eBook.
• Assess and Learn: This section contains the post-test, and Learning Curve assessments. Completing this will provide a study plan and a measure of how well you have learnt the subject matter.
• Test: This section contains the quizzes and examinations. Attempt these only after you have learnt the material.

The Lesson Plans provide a structure that will prove beneficial for most students. However, to learn and do well, requires time and effort. As such, please try to put consistent and timely effort toward your learning.

A short video walkthrough explaining the materials available for this course on StatsPortal can be found here.

Class Time and Office Hours

There are no scheduled class times or office hours.  This class is completely web based. There are several ways to ask for help. You can either email me directly (mshanker@kent.edu), or preferably, ask questions in the discussion forum on StatsPortal. Asking questions on the forum allows us to respond and build knowledge so that others in the class may benefit. In addition, each week in a lecture labelled “office hours”, I will summarize the discussions in the forums, and also clarify content that students may be having trouble with. As such, I have created discussion forums for each major topic of the class. I will typically post my “office hours” lecture on Thursday or Friday of the week.

Statistical Software

This course makes extensive use of statistical software. You have two options. Use Crunchit! or JMP. Each has its advantages, but both of them are free. The table below summarizes the advantages and disadvantages of each software as pertaining to this course.

If you plan on using multiple computers while taking this course, I would recommend Crunchit!. Otherwise, either Crunchit! or JMP will work equally well.

JMP is free to all Kent State Students and has been developed for statistical analysis and data exploration. To get a copy of JMP, please go to http://www.kent.edu/is/helpdesk/sas.cfm. University licensing provides this software at no cost to you. Please access the extensive help menu system in JMP to learn how to use it. A complimentary webcast on learning JMP is being offered. Click here to register. There is also an online library of tutorials on using JMP.

Course Content

Part I: Looking at Data

• Chapter 1: Looking at Data - Distributions
• Chapter 2: Looking at Data - Relationships
• Chapter 3: Producing Data

Part II: Probability and Inference

• Chapter 4: Probability (Sections 4.1 and 4.3)
• Chapter 5: Sampling Distributions
• Chapter 6: Introduction to Inference (Sections 6.1, 6.2, and 6.3)
• Chapter 7: Inference for Distributions (Section 7.1)
• Chapter 8: Inference for Proportions (Section 8.1)

Part III: Topics in Inference

• Chapter 10: Inference for Regression
• Chapter 11: Multiple Linear Regression

Assessments

There are three types of graded assessments in this course: Quizzes, Examinations, and Learning Curve.

There will be 10 Learning Curve assignments, 9 quizzes, and a final examination.  All assessments will be taken online, and are best taken using a standards-compliant web browser like Mozilla Firefox. Examinations and quizzes will consist of multiple choice, true or false, fill-in-the blanks, short-answer, matching, and calculation type questions. All assessments are open-book, open notes, but cheating in any form will result in a failing grade for the course. As such, while you are allowed to use books and notes for the tests, it is cheating if you ask other students to help you while taking the tests.

Learning Curve: In this activity you receive points by reaching a Target Score. Activities are graded on a pass/fail basis. Every student who completes the activity by reaching the target score receives a grade of 100%. Students who start but don't complete the activity remain at 0%. There is one activity for each chapter. The target score and total points that can be earned vary for each activity, but the total maximum points from all Learning Curve (LC) activities is 975.

Quizzes: There are 9 quizzes for this class. The amount of time allotted for each quiz may vary, but will typically be around 40 minutes. You will have one attempt to take each quiz. While the score from the quizzes will be known immediately, the results will be available only after the quizzes close for all students. Quizzes are not proctored, but once a quiz has been started, you need to complete it in one sitting. The total maximum points that can be earned from quizzes is 775.

Examinations: There will be a final examination worth 400 points. You will have one attempt to take the final exam, and once you start the examination, you need to complete it in one sitting. The exam will take approximately 90 minutes.

Assessment Schedule

The following table gives the topics covered, the assessments given over those topics, the maximum points for each assessment, and the due dates. All assessments end at 11:55 p.m. ET on their scheduled due date. Further, please remember to complete all requirements for the course by 13 July 2014.

Note: All chapters except Chapter 11 have two assessments, a quiz and a learning curve activity.

Grades

The maximum possible score for this class is 2150 (975 from Learning Curve, 775 from quizzes, and 400 from the final examination). Your final grade will depend on the grading scale given below.

· Scores below 1376 results in an “F”.

· None of the assessments can be made up. Missed assessments will receive a score of zero.

· Please print and keep a copy of your assessments. That will be the proof I will require if there are any disputes about scores. You will have one week after receiving the score for each assessment to request any corrections.

Extra Credit

Statistical literacy, reasoning, and thinking are important aspects of this course. By statistical literacy we refer to the basic understanding of the language and tools of statistics. Statistical reasoning refers to the way students understand and make sense of statistical information, and finally, statistical thinking refers to why and how statistical investigations are carried out. By taking this course, I am hoping that your statistical literacy, reasoning, and thinking will improve. To determine this, you will have the opportunity to take two surveys. Details are given below, but please note the following:

• You will be given 25 extra credit points for taking the pre-test survey. The number of points for the post-test survey depends on how well you perform in the post-test.
• To ensure accuracy of credit, please enter your first and last name in the survey exactly as given in your Kent records. That way, I can give credit to the right student.
• Each survey takes between 30 and 40 minutes.

Pretest Survey: Please take this survey before you start work on your course. This is a pretest survey, that is, it measures your knowledge before you learn the concepts in this course. You will get 25 extra credit points for this survey. The number of points is not affected by your performance in the survey. To access this survey:

• Go to https://apps3.cehd.umn.edu/artist/user/scale_select.html  
• Enter YEM7292PMB for Access Code.

This survey is available only between 00:05 on 06-05-2014 and 23:55 on 06-15-2014 (EASTERN).

Posttest Survey: Please take this survey after you have completed all assessments. This is a posttest survey. The number of extra credit points you will receive depends on your performance on the survey. Students receiving less than 50% will receive no points. Students with more than 80% score will receive 50 extra credit points. Scores between 50% and 80% will receive between 25 and 50 points interpolated linearly.  To access this survey:

1. Go to https://apps3.cehd.umn.edu/artist/user/scale_select.html
2. Enter IBP1952NGI for Access Code

This survey is available only between 00:05 on 07-07-2014 and 23:55 on 07-13-2014 (EASTERN).

Appendix

Technical Support

Technical support for StatsPortal is available at 1-800-936-6899. You can also submit a tech support ticket. Click on HELP (upper right corner) once you log into StatsPortal to get more information. Ensure that your system meets the technical requirements by doing a system check (http://angel.bfwpub.com/syscheck/index.html).

Web Links

• StatsPortal (http://courses.bfwpub.com/ips7e.php)
• StatsPortal Video Walkthrough (http://tiny.cc/2405660_SPT)
• JMP Tutorials (http://www.jmp.com/academic/learning_library.shtml)
• Blackboard Learn (https://learn.kent.edu.)

Learning Outcomes

1. Examine distributions.

1. Summarize and describe the distribution of a categorical variable in context.
2. Generate and interpret several different graphical displays of the distribution of a quantitative variable (histogram, stemplot, boxplot).
3. Summarize and describe the distribution of a quantitative variable in context: a) describe the overall pattern, b) describe striking deviations from the pattern.
4. Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts.
5. Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context.
6. Apply the standard deviation rule to the special case of distributions having the "normal" shape.
1. Explore relationships between variables using graphical and numerical measures.

 .                    Classify a data analysis situation (involving two variables) according to the "role-type classification," and state the appropriate display and/or numerical measures that should be used in order to summarize the data.

a.                   Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context.

b.                  Produce a two-way table, and interpret the information stored in it about the association between two categorical variables by comparing conditional percentages.

c.                   Graphically display the relationship between two quantitative variables and describe: a) the overall pattern, and b) striking deviations from the pattern.

d.                  Interpret the value of the correlation coefficient, and be aware of its limitations as a numerical measure of the association between two quantitative variables.

e.                   In the special case of linear relationship, use the least squares regression line as a summary of the overall pattern, and use it to make predictions.

f.                   Recognize the distinction between association and causation, and identify potential lurking variables for explaining an observed relationship.

g.                   Recognize and explain the phenomenon of Simpson's Paradox as it relates to interpreting the relationship between two variables.

3. Sampling. Examine methods of drawing samples from populations

 .                    Identify the sampling method used in a study and discuss its implications and potential limitations.

a.                   Critically evaluate the reliability and validity of results published in mainstream media.

4. Designing Studies. Distinguish between multiple studies, and learn details about each study design.

 .                    Identify the design of a study (controlled experiment vs. observational study) and other features of the study design (randomized, blind etc.).

a.                   Explain how the study design impacts the types of conclusions that can be drawn.

b.                  Determine how the features of a survey impact the collected data and the accuracy of the data.

5. Probability: Concepts and properties
6. Random Variables: Discrete and continuous. Using distributions of random variables to compute probabilities.
7. Sampling distributions of the sample mean and proportion.

 .                    Identify and distinguish between a parameter and a statistic.

a.                   Explain the concepts of sampling variability and sampling distribution.

b.                  Apply the sampling distribution of the sample proportion (when appropriate). In particular, be able to identify unusual samples from a given population.

c.                   Apply the sampling distribution of the sample mean as summarized by the Central Limit Theorem (when appropriate). In particular, be able to identify unusual samples from a given population.

8. Estimation: Determine point and interval estimates for the population mean and proportion

 .                    Determine point estimates in simple cases, and make the connection between the sampling distribution of a statistic, and its properties as a point estimator.

a.                   Explain what a confidence interval represents and determine how changes in sample size and confidence level affect the precision of the confidence interval.

b.                  Find confidence intervals for the population mean and the population proportion (when certain conditions are met), and perform sample size calculations.

9. Hypothesis Testing: Logic and process. Conduct tests for the population mean and proportion. Understand relationship between hypothesis testing and estimation.

 .                    Explain the logic behind and the process of hypotheses testing. In particular, explain what the p-value is and how it is used to draw conclusions.

a.                   In a given context, specify the null and alternative hypotheses for the population proportion and mean.

b.                  Carry out hypothesis testing for the population proportion and mean (when appropriate), and draw conclusions in context.

c.                   Apply the concepts of: sample size, statistical significance vs. practical importance, and the relationship between hypothesis testing and confidence intervals.

d.                  Determine the likelihood of making type I and type II errors, and explain how to reduce them, in context.

10. Inference for Regression. Construct the simple linear regression model, and develop confidence intervals and significance tests for the parameter estimates. Introduce the analysis of variance for regression.

 .                    Introduce the statistical model for linear regression, and estimate the regression parameters.

a.                   Develop confidence interval and significance tests for the intercept and slope in a linear regression.

b.                  Develop confidence intervals for a mean response and a prediction interval for a future observation

c.                   Develop the analysis of variance for regression, including the partitioning of sums of squares, degrees of freedom and mean squares. Present the ANOVA F test.

11. Multiple Regression. Present the multiple linear regression model, and the estimation of its parameters. Obtain confidence intervals and significance tests for the regression coefficients. Present the ANOVA table for multiple regression.

 .                    Present the multiple linear regression model, and the estimation of the model parameters.

a.                   Present the confidence interval and significance tests for the regression coefficients.

b.                  Present the ANOVA table for multiple regression. Discuss the F test, and the interpretations of the t and F tests.