Resource Economics 212H- Spring 2015: Introductory Statistics for the Social Sciences

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1 Resource Economics 212H- Spring 2015: Introductory Statistics for the Social Sciences Mondays & Wednesdays 2:30-3:45p, Flint Laboratory 103 Course Objectives Instructor: Kelly Hellman Office Hours: MW 1-2:15 and by appointment. Office Hours Location: Stockbridge Hall *Please allow 24 hours for replies to s. Statistics is a field of study, or science, in which we make inferences about populations based on a sample of data. There are two major fields in statistics: mathematical statistics deals with the theoretical underpinnings of the subject and focuses on developing new statistical methods; applied statistics deals with the application of statistical methods to solve problems in other fields of study. This course will focus on the application of statistical methods to Social Sciences and Business. When you complete this course you will have a working knowledge of the methods and skills needed to organize data, conduct meaningful analysis, and draw inferences from a sample about a population. Knowledge of statistics learned in this course allows you to experience the world in a different light. The skills you will learn can be used in your everyday decision-making and communication. Our broad goal is that you become an active consumer of statistics and a practitioner of statistical analysis. To accomplish this very broad goal, you will need to learn: The meaning and appropriate uses of the two broad statistical methodologies: descriptive and inferential. The meaning of statistics commonly found in the popular press and to appreciate the value that those statistics provide to articles you read. When statistics are used in a misleading manner and what statistic or statistics would be appropriate. The construct of different data sets, the types of data included, and which data are appropriate to answer research questions or support policy statements. The development and use of appropriate descriptive statistics for both qualitative and quantitative data analysis. The proper interpretations for qualitative and quantitative data displays (graphs, charts, etc.). The proper applications and interpretations of numeric summary statistics. How to appropriately use sample data and statistics to make inferences about the properties or characteristics of a population. ResEcon212H Fall

2 Course Description In this course we will focus on learning and applying basic statistical methods. You are responsible for reviewing the relevant material BEFORE attending class. You will prepare for lectures and in-class activities during the prior week by completing pre-lecture assignments. Generally, we will spend one class reviewing a topic and a second class applying and discussing statistical methods during computer lab sessions. During the application class periods, you will complete lab assignments and will complete a post-lab assignment outside of class. You will also collaborate with classmates outside of class on a team project to demonstrate knowledge of statistical methods using empirical data chosen by your team. The team project is also assigned to give you and your team members the opportunity to learn from the experience of working in a group setting. Team members will provide constructive feedback to one other to enhance the experience. Topics Covered: Topic 1: Introduction to Statistics (Chapter 1) Topic 2: Collecting Data & Data Types (Chapter 2) Topic 3: Descriptive Statistics (Chapters 3 & 4) Univariate Visual Univariate Numerical Bivariate Visual & Numerical Topic 4: Probability Rules (Chapter 5) Topic 5: Discrete Probability Distributions (Chapter 6) Topic 6: Continuous Probability Distributions (Chapter 7) Topic 7: Inferential Statistics (Chapter 8 & 9) Sampling Distribution Confidence Intervals One-Sample Hypothesis Testing Topic 8: More Inferential Statistics: Two-Sample Hypothesis Testing (Supplemental Reading) hhhh ResEcon212H Fall

3 Required Materials TEXTBOOK - Edition 4 of Applied Statistics in Business & Economics - Sold by publisher online at: - Comes with book, Minitab software & Connect code (not required) - $ shipping as of 09/02/15 - This custom edition includes only the chapters of the complete b o book (chp. 1-9). These are the only chapters we will cover in R e s E ResEcon212H. The remaining chapters of the complete book will b e be covered in ResEcon213. You can buy a used copy without Connect or Minitab, please just make sure it is the fourth edition. NOTE: If you search for and try to buy the textbook through the Amazon bookstore, it will have you purchase the entire book. You do NOT need the entire book for ResEcon 212 and can purchase the shortened volume with only chapters 1-9 at a reduced price using the link above. MOODLE The following with be posted on Moodle on a weekly: Additional resources on Moodle: - Lecture slides - Project materials - Pre-Lecture assignments/answer keys - Question/answer forum - In-Class lab assignments/answer keys - Post-Lab assignments/answer keys - Assignment grades STATISTICAL SOFTWARE While our textbook uses both Excel and MINITAB, we use Microsoft Excel predominantly in this course. For Mac users: MINITAB runs on a Windows platform only. It is possible to dual boot a Mac in order to run such software; however it is not necessary for this class. If you do not wish to run either Excel or MINITAB on your personal computer, both the Excel and MINITAB are available at any UMass PC lab. Please be aware, however, that you will be expected to complete out of class assignments using Excel, and please ensure that you make the proper arrangements to complete these assignments. Additionally UMass students can get Microsoft Office 365 Education free through the university: ResEcon212H Fall

4 CALCULATOR For exams you must use a calculator, not a Cell Phone, a Palm, or a Pocket PC. Please note that you cannot share calculators during exams. Other Materials CONNECT Connect is NOT required for this course but comes with your textbook purchase if you buy it new. You can use Connect to complete problems for extra practice, however- THERE WILL BE NO CREDIT GIVEN FOR ASSIGNMENTS COMPLETED IN CONNECT. If you choose to practice using Connect, you will need to register for Connect using a code that comes with the textbook you purchased. Connect also has an option for a Courtesy Trial that you can register for free until add/drop. You can register for Connect using the link posted on Moodle. If you have any issues with Connect you can diagnose the problem by clicking on Troubleshoot at the very bottom right of the Connect website. If you cannot resolve the issue please contact McGraw-Hill tech support: Website- or call When you contact McGraw-Hill with a question, please write down the case number they give you. If you have any questions you will be responsible for following up with them. MOODLE QUESTION & ANSWER FORUM The forum is designed for students to ask questions about the material or course that could benefit other students. The forum is publically available to all students in the class. Please feel free to post questions and/or responses to other students at any time. We will moderate the forum & answer questions within 24 hrs. Please do not post any private questions or information and be respectful. Grading Policy Pre-Lectures 10% In-Class Work 15% Post-Labs 10% Midterm 20% Final 20% Team Project 25% Minimum Grade Guarantee: Grades are determined by your performance on all components listed above. There are no extra credit activities in this class. To allow you to check your grade-to-date, we will abide by the following minimum grade cutoff points based on a percentage of the total points available: A = 92, A- = 89, B+ = 86, B = 82, B- = 78, C+ = 74, C = 70, C- = 66, D+ = 62, D = 58, and F<58 ResEcon212H Fall

5 Description of Grading Components Late in-class or out-of-class work is not accepted for credit without an acceptable and documented University excused absence.* If you do not have a valid excuse for an absence or late submission, you are welcome to turn in the assignment after the due date for feedback. We will also take these submissions into consideration when determining final grades if you are between two grades. *Please visit the following website for specifics on accepted University excused absences: ***Assignments due in class are due at the beginning of the class period!*** Please be extra cautious with any assignments that are submitted on Moodle. Submit assignments with enough time to account for technical issues. If you encounter an issue, immediately the assignment before the deadline to khellman@resecon.umass.edu. Pre-Lectures: Weekly pre-lecture assignments are due each week prior to the start of a new topic. You will need to review the materials posted on Moodle along with your textbook to complete the assignment. You are welcome to work with your peers and consult us when working on the pre-lectures; however, make sure that each student turns in a unique submission! The goal of these assignments is to ensure preparation before class so that our class time can be used to develop deeper understanding of the material. Your lowest pre-lecture assignment at the end of the semester will be dropped. Your combined score from these weekly assignments will account for 10% of your course grade. In-Class Work: There are two components to the in-class work portion of your final grade. Approximately 5% will be attributed to participation during lecture classes. Upon completing the lectures on new material, we will spend one class period in the computer lab using example data to apply lecture concepts. 10% of the in-class work component will comprise graded lab assignments, which are due during that class period. *You must be in class to complete these assignments. Your lowest lab assignment at the end of the semester will be dropped. Your in-class participation and lab assignments will account for 15% of your course grade. Post-Labs: To solidify the concepts, you will complete weekly post-lab assignments, which are due 1 week after completion of the relevant in-class lab assignment. Please do not consult your peers on these assignments, but feel free to come to us with any questions. Your lowest post-lab assignment at the end of the semester will be dropped. Your combined score from these weekly assignments will account for 10% of your course grade. ResEcon212H Fall

6 Final Project: The object of this course is to guide you in becoming a consumer and practitioner of statistics. To help achieve this goal, you will complete a final project in the form of a statistical report with your peers. You will explore research questions that you all come up with using real world data. Your team will need to meet outside of class to complete the project. At the end of the semester, each team will present their research to the class and submits a report containing the following sections: SECTION CONTENTS 1) Introduction Background Research questions 2) Methodology Data collection Descriptive methods Inferential methods 3) Data & Results Describe data visually Describe data numerically Probability tables/distributions Confidence intervals Hypothesis testing 4) Conclusions Summarization of findings Your project will be turned in by your team in a series of drafts. You will turn in a final paper before finals week and present your work to the class during the last week of classes. The final project accounts for 25% of your final grade, with the breakdown for part of the project below: Submission SECTIONS DUE DUE DATE % POINTS Draft I Choose data set and write an Fri. Sep % introduction to the data. Draft II Introduction and research questions. Fri. Oct. 2 5% Draft III Methods/results for descriptive stats. Fri. Nov. 6 5% Draft IV Methods/results for inferential stats. Fri. Dec. 4 5% Final All sections. Sun Dec. 13 5% In-Class Presentation Wed Dec % During the weeks specified in the class schedule, after submissions of drafts II-IV, each team is required to meet with us to discuss their project submission. Midterm Exam There will be 1 midterm examination given in class on Thursday, October 15 th from 6-9pm, location TBA. Please mark your calendars. No make-up exams will be given for work or personal conflicts; you must be able to take this exam as scheduled. Your midterm exam accounts for 20% of your final grade. ResEcon 212 Spring

7 Final Exam: A comprehensive final exam will be given during the final examination period, on Thursday, December 17. Your final exam accounts for 20% of your final grade. Additional Course Policies Academic Dishonesty Policy Cheating will not be tolerated in any shape or form. Cheating includes but is not limited to turning in the same assignment as another student if you are required to turn in separate papers and plagiarizing from outside sources. If you're caught cheating we will follow the University's established procedures to pursue the matter to the fullest extent possible (see your "Undergraduate Rights and Responsibilities" handbook). No two assignments should be identical. Many times you will be allowed and encouraged to work with your classmates; however, each individual must turn in a reflection of their own work in their own words. Additionally, writing anyone s name who was not present in class on any in-class activity is cheating. When writing your final project paper you must properly cite all sources and use quotations for words repeated verbatim form a source. You should also be care to summarize information from sources and not simply change words here and there. DO NOT COPY & PASTE FROM THE INTERNET. THIS IS PLAGARISM, AND PLAGARISM WILL NOT BE TOLERATED UNDER ANY CIRCUMSTANCES. Learning Accommodations If you have a physical, psychological, medical or learning disability that may impact on your ability to carry out assigned course work, we urge you to contact UMass Disability Services at They will review your concerns and determine, with you, what accommodations are necessary and appropriate. All information and documentation of disability is confidential. Attendance & Class Preparation: Class attendance is expected & critical to success in this course. Please be aware that class attendance and participation comprises 15% of your final grade. If you choose to attend class, we insist that you be on time and refrain from visiting with your neighbors. Disruptive behavior will not be tolerated or ignored. Students who do not attend class cannot expect individual tutoring from the instructor. If you miss a class without an acceptable University excuse, you are still responsible for the material covered in and outside of class. Additionally, it is your responsibility find out about announcements made in class. All announcements & lectures notes will be posted on Moodle in a timely manner. ResEcon 212 Spring

8 Date Class Topics Readings Assignments Due Wed. Jan. 21 Introduction to Statistics Text Chp 1, Chp 2.3 Mon. Jan. 26 LAB DAY Lab #1: Data Exploration Text Chp , Review data sets on Moodle Wed. Jan. 28 Data Collection & Types of Data Text Chp 2 Pre-Lecture #1 due in class Mon. Feb. 2 LAB DAY Lab #2.1: Univariate Graphs & Charts Text Chp 3.2, , 3.9 Wed. Feb. 4 Descriptive Stats: Univariate Visual Displays Text Chp 3.2, , 3.9 Pre-Lecture # , Postlab #1 due in class Wed. Feb. 11 Univariate Numerical Measures Text Chp Pre-Lecture #2.3, Post-lab #2.1 due in class Mon. Feb. 16 PRESIDENTS DAY-NO CLASSES Tue. Feb. 17 LAB DAY Lab #2.2: Univariate Numerical Text Chp MONDAY SCHEDULE Wed. Feb. 18 Univariate Numerical Cont d; Bivariate Visual & Numerical Text Chp 3.7, Pre-Lecture #2.3.1 due in class Mon. Feb. 23 LAB DAY Lab#2.3: Bivariate Visual & Numerical Text Chp 3.7, 4.6 Post-Lab #2.2 due on Moodle Wed. Feb. 25 Probability Rules Text Chp 5 Pre-Lecture #3 due by class Mon. Mar. 2 LAB DAY Lab #3: Probability Rules Text Chp 5 Post-Lab #2.3 due by class Wed. Mar. 4 MIDTERM IN CLASS Sun. Mar. 8 Draft I 11:55p Mar Team Meetings with Instructor to Review Draft I Mon. Mar. 9 Discrete Probability Text Chp Wed. Mar 11 Continuous Probability Distributions Text Mar SPRING BREAK Mon. Mar. 23 LAB DAY Lab #4-5: Discrete & Continuous Text Chp Pre-Lecture #4-5 due by class Probability Distributions Text Chp Wed. Mar. 25 Sampling Distributions, Estimation & Text Chp Pre-Lecture #6.1 due by class Confidence Intervals Mon. Mar. 30 LAB DAY Lab #6.1: Sampling Distributions Text Chp Post-Lab #4-5 due by class Wed. Apr. 1 Confidence Intervals Text Chp Pre-Lecture #6.2 due by class Mon. Apr. 6 LAB DAY Lab #6.2: Confidence Intervals Text Chp Post-Lab #6.1 due by class Wed. Apr. 8 Confidence Intervals Text Chp Pre-Lecture #7.1 due by class Mon. Apr. 13 One Sample Hypothesis Tests Text Chp Post-Lab #6.2 due by class Wed. Apr. 15 One & Two Sample Hypothesis Tests Text ; Pre-Lecture #7.2 due by class Moodle Post Fri. Apr. 17 Draft II 11:55p Mon. Apr. 20 PATRIOT S DAY- NO CLASSES Apr Team Meetings with Instructor to Review Draft II Wed. Apr. 22 Lab 7: One-Sample Hypothesis Tests Text Chp Pre-Lecture #8 due by class MONDAY SCHEDULE LAB DAY Mon. Apr. 27 LAB DAY Project Work Day Wed. Apr. 29 TEAM PROJECT PRESENTATIONS IN CLASS Post-Lab #7 due by class Tues. May 5 FINAL 4-8p, Location TBA Fri. May 8 Team Project 11:55p ResEcon 212 Spring

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