Welcome to MTH214

• Mikael Vejdemo-Johansson
• Office: 1S-208, office hours MW 12.45-2.15

• Email: Mikael.VejdemoJohansson@csi.cuny.edu - use it!

• Lecture: M 2.30-4.25, 1S-115

• Lab: W 2.30-4.25, 1S-108

• Course webpage: http://www.math.csi.cuny.edu/~mvj/MTH214
  Contains all course material, labs, lecture slides, report grading criteria…
• Lecture slides: http://www.math.csi.cuny.edu/~mvj/MTH214/lectures/Lecture1.html

• Lecture slide source code: http://www.math.csi.cuny.edu/~mvj/MTH214/lectures/Lecture1.Rmd

Books and schedule

We will use 3 different books, 2 are available for free as ebooks through the library:

• Introduction to the Practice of Statistics. (9th ed; used copies are fine); The R Software; ggplot2

Schedule overview

• Before Week 2: pick a dataset. You will be working with this dataset all semester.
• Week 1-7: Descriptive statistics.
• Write a report that describes your dataset
• Detailed grading criteria: http://www.math.csi.cuny.edu/~mvj/MTH214/pages/first-report-criteria.html
• Week 8-16: Inferential statistics.
• Formulate hypotheses about your data and write a report that tests your hypotheses
• Detailed grading criteria: http://www.math.csi.cuny.edu/~mvj/MTH214/pages/second-report-criteria.html

Course grade

Course grade will be composed as

• 40% First report
• 40% Second report
• 10% Labs
• 5% Homework
• 5% Final exam

Course goals

This course will emphasize computers and practical statistics. After passing the course you will be able to

• Load and clean data into the statistics program R
• Perform statistical analyses
• Interpret statistical analyses
• Determine whether an analysis is correct / know what is required for a test to apply
• Communicate your results

To get you comfortable with efficient communication, homework and labs should be done using RMarkdown in RStudio. All datasets used in the Introduction to the Practice of Statistics book is already available in your RStudio login.

Form groups of 4

Discuss and list:

• Why are you taking this class?
• What do you hope to get out of it?
• What is statistics?

Continue in groups of 4

Discuss and list:

• What is data?
• Where does data come from?
• What forms of presenting or communicating data do you know?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Examples in the wild

What does the chart show? Does it contain enough information? What else would have been needed? Is it honest and accurate?

Types of Data

We will focus on working on Tidy data:

• Each variable in its own column
• Each observation in its own row

Variables can be

• Numeric (real, integer)
• Logical (truth values - TRUE or FALSE)
• Categorical (takes on a few specific values), called factor in R
• Character strings (pieces of text)
• Dates or Times