Lecture 0: Introduction Statistics 101 Thomas Leininger May 15, - - PowerPoint PPT Presentation

Lecture 0: Introduction

Statistics 101

Thomas Leininger

May 15, 2013

Syllabus & policies Logistics

General Info

Professor: Thomas Leininger - thomas.leininger@duke.edu Old Chemistry 114 Lecture: MTWThF, 12:30–1:45pm, Old Chem 025 Lab: TTh, 2–3pm, Link Classroom 6 Textbook OpenIntro Statistics Diez, Barr, C ¸ etinkaya-Rundel CreateSpace, 2nd Edition, 2012 Calculator (Optional) You might need a four-function calculator that can do square roots for this class. No limitation on the type of calculator you can use.

Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 1 / 31

Syllabus & policies Logistics

Webpage

http://stat.duke.edu/ ∼tjl13/s101/sta101.html All announcements and assignments will be posted on this website under the schedule tab.

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Syllabus & policies Logistics

Grading

• Problem sets: 20%
• Labs: 15%
• Quizzes: 10%
• Project: 20%
• Midterm: 15%
• Final: 20%

Grades curved at the end of the course after overall averages have been calculated.

Average of 90-100 guaranteed A-. Average of 80-90 guaranteed B-. Average of 70-80 guaranteed C-.

The more evidence there is that the class has mastered the material, the more generous the curve will be.

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Syllabus & policies Details

Course goals & objectives

1

Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.

2

Use statistical software to summarize data numerically and visually, and to perform data analysis.

3

Have a conceptual understanding of the unified nature of statistical inference.

4

Apply estimation and testing methods to analyze single variables

• r the relationship between two variables in order to understand

natural phenomena and make data-based decisions.

5

Model numerical response variables using a single explanatory variable or multiple explanatory variables in order to investigate relationships between variables.

6

Interpret results correctly, effectively, and in context without relying on statistical jargon.

7

Critique data-based claims and evaluate data-based decisions.

8

Complete a research project employing statistical inference.

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Syllabus & policies Details

Units and major topics

Unit 1 Introduction to data: Observational studies and non-causal inference, principles of experimental design and causal inference, exploratory data analysis: description, summary and visualization, introduction to statistical inference. Unit 2 Probability and distributions: The basics of probability and chance processes, Bayesian perspective in statistical inference, the normal distribution. Unit 3 Framework for inference: Central Limit Theorem and sampling distributions Unit 4 Statistical inference for numerical variables Unit 5 Statistical inference for categorical variables Unit 6 Simple linear regression: Bivariate correlation and causality, introduction to modeling Unit 7 Multiple linear regression: More advanced modeling

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Syllabus & policies Details

Lectures

Lecture slides will be posted on the course webpage (under schedule) by noon the day of the course (hopefully). In order to be able to keep up with the pace of the course and not fall behind you must attend the lectures. Introduction of concepts as well as hands-on activities and exercises to complement them.

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Syllabus & policies Details

Problem sets

Objective: Help you develop a more in-depth understanding of the material and help you prepare for exams and projects. Questions from the textbook. Due at the beginning of class on the due date. Generally assigned on Tuesdays and Fridays. Show all your work to receive credit. Welcomed and encouraged to work with others, but turn in your

• wn work.

Lowest score will be dropped. No make-ups. Excused absences do not excuse homework.

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Syllabus & policies Details

Labs

Objective: Give you hands on experience with data analysis using a statistical software and provide you with tools for the projects. http://beta.rstudio.org Labs will be on Tuesday and Thursday in the Link. You can email me your lab report or turn it in at class. Any labs during the week are due the following Monday by the beginning of class. Add your gmail address to Google doc by 4pm today to create an RStudio account. Can be done in teams of 2–3. Lowest lab score will be dropped.

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Syllabus & policies Details

Projects

Objective: Give you independent, applied research experience using real data and statistical methods. choose a research question, find data, analyze it, write up your results. statistical inference exploring the distributional characteristics of

• ne variable or relationship between two variables.

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Syllabus & policies Details

Quizzes

Objective: Help you identify any knowledge gaps and help me pace the class. These will be given on Fridays (except the day of the midterm). You are welcome to use notes or the book.

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Syllabus & policies Details

Exams

Midterm: Friday, June 7 Final: Wednesday, June 26, 9am-12pm (Cumulative) Exam dates cannot be changed. No make-up exams will be

• given. If you cannot take the exams on these dates you need to

talk to me by the Add/Drop deadline (this Friday). You must bring a calculator to the exams (no cell phones, iPods, etc.) and you are also allowed to bring one sheet of notes (“cheat sheet”). This sheet must be no larger than 8 1

2” × 11” and

must be prepared by you (no photocopies). You may use both sides of the sheet.

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Syllabus & policies Details

Work load

You are expected to put in 2-3 hours of work outside of class every

• day. Some of you will do well with less time than this, and some of

you will need more.

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Syllabus & policies Support

Email & office hours

I will regularly send announcements by email, so make sure to check your email daily. While email is the quickest way to reach me outside of class, it is much more efficient to answer most statistical questions in person. I will hold office hours on Mondays and Wednesdays from 2–4pm in Old Chem 114.

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Syllabus & policies Support

Other learning resources

Aside from my office hours, you can also make use of the Academic Resource Center( http://web.duke.edu/arc ).

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Syllabus & policies Support

Students with disabilities

Students with disabilities who believe they may need accommodations in this class are encouraged to contact the Student Disability Access Office at (919) 668-1267 as soon as possible to better ensure that such accommodations can be made.

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Syllabus & policies Policies

Policies I

Late work policy for problem sets and labs reports:

after class on due date: lose 10% of points next day: lose 20% of points later than next day: lose all points

Late work policy for projects: 10% off for each day late. There will be no make-up for labs, problem sets, projects, or exams. If a quiz or the midterm exam must be missed, absence must be

• fficially excused in advance, in which case the missing exam

score will be imputed using the final exam score. The final exam must be taken at the stated time.

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Syllabus & policies Policies

Policies II

You must take the final exam and turn in the project in order to pass this course. Regrade requests must be made within one week of when the assignment is returned, and must be submitted in writing.

These will be honored if points were tallied incorrectly, or if you feel your answer is correct but it was marked wrong. No regrade will be made to alter the number of points deducted for a mistake. There will be no grade changes after the final exam.

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Syllabus & policies Policies

Academic Dishonesty

Any form of academic dishonesty will result in an immediate 0 on the given assignment and will be reported to the Office of Student

• Conduct. Additional penalties may also be assessed if deemed
• appropriate. If you have any questions about whether something is or

is not allowed, ask me beforehand. Some examples: Use of disallowed materials (including any form of communication with classmates or looking at a classmate ˜ Os work) during exams. Plagiarism of any kind. Use of outside answer keys or solution manuals for the homework.

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Syllabus & policies Tips

Tips for success

1

Read along in the book to supplement the information in the lectures.

2

Be an active participant during lectures and labs.

3

Ask questions—during class or office hours, or by email. Ask your classmates too!

4

Do the problem sets—start early and make sure you attempt and understand all questions.

5

Start your project early and allow adequate time to complete it.

6

Give yourself plenty of time time to prepare a good cheat sheet for exams. This requires going through the material and taking the time to review concepts that you’re not comfortable with.

7

Do not procrastinate—don’t let a few days go by with unanswered questions as it will just make the following material even more difficult to follow.

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To do

To do

Download or purchase the textbook. Add your Gmail address to the Google Doc Read the syllabus and let me know if you have any questions. Start reviewing the material in the book for tomorrow’s lecture.

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Statistics and the Scientific Method

Statistics and the Scientific Method

From Universe Today - http://www.universetoday.com/74036/what-are-the-steps-of-the-scientific-method/ Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 21 / 31

Examples Baby names

Baby names in the US

Each year the Social Security Administration collects and releases data on the how many babies are given a certain name. They released these data for years 1880 to 2011 for each gender. For privacy reasons they restrict the list of names to those with at least 5 occurrences.

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Examples Baby names

Top 10 Baby Names For 2011

http://www.ssa.gov/oact/babynames Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 23 / 31

Examples Baby names

Jac...

Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 24 / 31

Examples Geotagged data

Geotagged data

Question Do you geotag your posts on social networking sites, like Facebook, Twitter, Instagram, etc.?

Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 25 / 31

Examples Geotagged data

Map based on Flickr tags

http://aaronstraupcope.com Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 26 / 31

Examples 538

The most famous statistician in the world

Source: http://fivethirtyeight.blogs.nytimes.com Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 27 / 31

Examples Online advertising

How do they know what ads to show me?

Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 28 / 31

Examples Links to blogs

Links to blogs

http://stat.duke.edu/courses/Spring13/sta101.001/links.html

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Why study statistics

[...], the study also warns there is a significant shortage

• f qualified workers to analyze

these data sets adequately. According to the report, a shortfall of about 140,000 to 190,000 individuals with analytical expertise is projected by 2018. The study also predicts a need for an additional 1.5 million managers and analysts by that same date to fully engage the true potential of the currently available data.

http://jobs.aol.com/articles/2011/08/10/data-scientist-the-hottest-job-you-havent-heard-of Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 30 / 31

Why study statistics http://www.dailymail.co.uk/news/article-2023514 Statistics 101 (Thomas Leininger) Lecture 0: Introduction May 15, 2013 31 / 31