Lecture_1 STATS

# Lecture_1 STATS - Introduction to Statistical Reasoning...

• Notes
• 71

This preview shows pages 1–17. Sign up to view the full content.

Introduction to Statistical Reasoning

This preview has intentionally blurred sections. Sign up to view the full version.

What do you think of when you hear statistics ”?

This preview has intentionally blurred sections. Sign up to view the full version.

To utilize statistics we need to understand: • how the data was collected • why it was collected • how to analyze and interpret the data appropriately
STATISTICS is a science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data INFERENTIAL STATISTICS STATISTICS DESCRIPTIVE STATISTICS

This preview has intentionally blurred sections. Sign up to view the full version.

A population is an entire group of which we want to characterize. A sample is a collection of observations on which we measure one or more characteristics. Population Sample Common Language:
The Environmental Protection Agency (EPA) tracks fuel economy of automobiles. Among the data they collect are the manufacturer (Ford, Toyota, etc.), vehicle type (car, SUV, etc.) weight, horsepower, and gas mileage (mpg) for city and highway driving. Five W’s WHO: Each model of automobile WHAT: Vehicle manufacturer, vehicle type, weight, horsepower, and gas mileage WHEN: Currently WHERE: United States WHY: By the EPA to tracks fuel economy of vehicles HOW: Collected from the manufacturers

This preview has intentionally blurred sections. Sign up to view the full version.

If you can not answer WHO and WHAT, you do not have a DATA
EXPLORING AND UNDERSTANDING DATA

This preview has intentionally blurred sections. Sign up to view the full version.

Types of Data Data Categorical Numerical Discrete Continuous Examples: Marital Status Are you registered to vote? Eye Color (Defined categories or groups) Examples: Number of Children Number of SMS per minute (Counted items) Examples: Weight Temperature (Measured characteristics)
CATEGORICAL (QUALITATIVE) DATA Can be separated into different categories that are distinguished by some nonnumeric characteristics Genders (male/female) Eyes color (blue, brown,grey etc) Vehicle type (car, SUV, VAN, truck) Opinion (yes/no) Size of soda (small, medium, large) Political affiliation (democrat, republican, independent, green party, other)

This preview has intentionally blurred sections. Sign up to view the full version.

There are two types of categorical variables: • Ordinal (arranged in a meaningful order) • Not ordinal (no meaningful order) Genders (male/female) Eyes color (blue, brown, grey etc) Vehicle type (car, SUV, VAN, truck) Opinion (yes/no) Size of soda (small, medium, large) Political affiliation (democrat, republican, independent, green party, other) What type of categorical variable are following:
QUANTITATIVE (NUMERICAL) DATA Consist of numbers representing counts or measurements Weight of cats (in pounds) Height of students (in inches) Household size (in persons) Age (in years) Distance from UCLA (in miles) Number of cars in the library parking lot

This preview has intentionally blurred sections. Sign up to view the full version.

There are two types of quantitative variables: • Continuous (lies on an interval scale with infinite possible values) • Discrete (space between each value, countable) What type of quantitative variable are following: Weight of cats (in pounds) Height of students (in inches) Household size (in persons) Age (in years) Distance from UCLA (in miles) Number of cars in the library parking lot
Describing Data There are two ways to describe a data set: • Graphs and Tables • Numbers Both are important for analyzing data

This preview has intentionally blurred sections. Sign up to view the full version.

Graphical Presentation of Data Data in raw form
This is the end of the preview. Sign up to access the rest of the document.
• Winter '08
• Liu
• Frequency, Frequency distribution, Bar chart, Histogram

{[ snackBarMessage ]}

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern