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Lecture1[1]

# Lecture1[1] - Lecture 1 Statistical Applications and Types...

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Statistical Applications and Types of Data Chapter 1 With Section 7.8 STAT 225, Dallas Bateman, Spring 2010 1 Lecture 1

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Basic Definitions Data measurements from which information and knowledge are derived Dataset a collection of data, usually put in table form Element a single cell in a dataset Observation a subject on which data is being collected, makes up the rows of a dataset Variable any characteristic of an observation, makes up the columns of a dataset STAT 225, Dallas Bateman, Spring 2010 2
Example of a dataset STAT 225, Dallas Bateman, Spring 2010 3 Variable Observation Element

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Types of Data Scales of Measurement Categorical Can be split into categories Nominal Ordinal Continuous Numerical, we can do math Interval Ratio STAT 225, Dallas Bateman, Spring 2010 4
Categorical Data Nominal Data Has NO order Examples: Gender Religion Race or Ethnicity Ordinal Data Has order Examples: Class (Freshman, Sophomore, Junior, Senior) Rate pain (none, moderate, severe) Favorite Taco Sauce (Hot, Medium, Mild) STAT 225, Dallas Bateman, Spring 2010 5

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Continuous Data Interval Data Differences are interpretable; no “natural” zero Examples: Temperature, Dates Ratio Data Differences and ratios are interpretable; natural zero Examples: Height, Weight, Age Hard to distinguish between interval and ratio; often referred to as “interval - ratio data” STAT 225, Dallas Bateman, Spring 2010 6
Quantitative vs. Qualitative Quantitative Analysis Analysis of numerical data Can be measured Length, time, speed, volume, cost, etc. Qualitative Analysis Analysis of words, pictures, or objects Can be observed but not measured Color, texture, smell, taste, beauty, etc. STAT 225, Dallas Bateman, Spring 2010 7

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Qualitative Brown hair Red tie Black shoes Good lookin ’ face! Quantitative 54 years old Starred in 20 movies Weight: 175 lbs Height: 5’ 10” Income: \$275,000.00 STAT 225, Dallas Bateman, Spring 2010 8
What type of variable is… smoking status?

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