Lecture_1 STATS

Lecture_1 STATS - Introduction to Statistical Reasoning...

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Introduction to Statistical Reasoning
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What do you think of when you hear statistics ”?
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To utilize statistics we need to understand: • how the data was collected • why it was collected • how to analyze and interpret the data appropriately
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STATISTICS is a science of conducting studies to collect, organize, summarize, analyze and draw conclusions from data INFERENTIAL STATISTICS STATISTICS DESCRIPTIVE STATISTICS
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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:
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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
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If you can not answer WHO and WHAT, you do not have a DATA
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EXPLORING AND UNDERSTANDING DATA
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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)
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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)
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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:
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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
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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
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Describing Data There are two ways to describe a data set: • Graphs and Tables • Numbers Both are important for analyzing data
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Lecture_1 STATS - Introduction to Statistical Reasoning...

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