Variables 9/12/2013. Readings Chapter 2 Measuring and Describing Variables (Pollock) (pp.32-33) Chapter 2 Descriptive Statistics (Pollock Workbook)

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Presentation transcript:

Variables 9/12/2013

Readings Chapter 2 Measuring and Describing Variables (Pollock) (pp.32-33) Chapter 2 Descriptive Statistics (Pollock Workbook)

Exam 1 9/19 In class exam. You do not need an exam book You can use a basic calculator

OPPORTUNITIES TO DISCUSS COURSE CONTENT

Office Hours For the Week When – Monday and Friday 10-12:00 – Tuesday 8-12 – And by appointment

Course Learning Objectives 1.Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design. 2.Students Will be able to interpret and explain empirical data.

Variables

Measured Concepts We need to operationalize concepts to test hypotheses Concept- Conceptual Definition- Operational- Definition- Operationalization- Variable

Four Categories of Variables

Categorical Nominal Name And provide valuevalue Ordinal Name Provide value And Order

CONTINUOUS VARIABLES

What makes them unique The values matter Your variable includes all possible values, not just the one’s that you assign. Name, order, and the distances between values matter.

Interval Level Variables The values matter at this level The distances matter The zero is arbitrary

Examples of Interval Scales

Ratio Variables The Full properties of numbers. Its measurement on Steroids Steroids A zero means the absence of a property Classify, order, set units of distance

Examples

Energy Use

Nominal, Ordinal, Ratio

Crime By Region

DESCRIPTIVE STATISTICS

Descriptive Statistics These simply describe the attributes of a single variable. You cannot test here (you need two variables) Why do them?

Categories of Descriptive Statistics Measures of Central Tendency The most common, the middle, the average Mean, Median and Mode Measures of Dispersion How wide is our range of data, how close to the middle are the values distributed Range, Variance, Standard Deviation

Frequency Distributions This Provides counts and percentages (relative frequencies) of the values for a given variable Computing a relative Frequency The Cumulative Percent is percentage of observations less than or equal to the category St. Edward’s Data

Lets Look at this one again

The Largest Hispanic Groups in America: Pie Charts

Immigration- Column/Bar Charts

The Mode the most frequent observation of the variable in a distribution Which category is most common There can be more than 1

Examples What are the Modes here? 1.110,

Advantages and Disadvantages Advantages of the Mode Disadvantages of the Mode

Where Parties Should Go in A Normal Distribution They Move To the Center, why?

What About A Bimodal Distribution?

Party Polarization

A polymodal System

THE MEDIAN

The Median It only tells us one thing – 50% above, 50% below the value that lies in the middle of the data when arranged in ascending order.

Examples The University of TexasTexas The Zip Code78704

About the Median Characteristics and problems of the median The middle observation = (N+1)/2 Three Examples – (133,113,112,95,94) – (27,12,78,104,45,34) – (105,102,101,92,91,80)

Locating the Median

Finding the Median location of median case (1747+1)/2 = 874 Where Does that case fall? – Case 1 through 534 = has value of 0 – Case 535 through 1747 = has value of 1 Case 874 is more than 535 and less than 1747 THE MEDIAN IS 1, the category is voted You can also look here for where 50% falls

Lets Try Again

The Answer location of median case (1454+1)/2 = Where Does that case fall? Cases 1 through 74 = has value of 1 Cases 75 through 502= has value of 2 Cases 503 through 1454= as a value of 3 Case is more than 503 THE MEDIAN IS 3, the category is not at all scientific The 50% falls in here

Median Voter Theory

THE MEAN

The Mean What is it How do you compute it?

About the Mean Characteristics of the Mean Problems of the Mean

An Example NameIncome Skipper50.00 Gilligan Mary Ann Professor Mrs. Howell Mr. Howell Ginger

Picking the Right Measure MeasureLevel of Analysis ModeNominal, Ordinal, Ratio, Interval MedianOrdinal, Ratio, Interval Mean Ratio, interval (sometimes ordinal, but super statistics nerds will say no)