Hypotheses
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Hypotheses. 9/4/2012. Readings. Chapter 1 The Measurement of Concepts (14-23) (Pollock ) Chapter 2 Measuring and Describing Variables (Pollock) (pp.28-31). Opportunities to discuss course content. Office Hours For the Week. When Wednesday 11-1 Thursday 8-12 And by appointment.

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Hypotheses

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Hypotheses

9/4/2012


Readings

  • Chapter 1 The Measurement of Concepts (14-23) (Pollock)

  • Chapter 2 Measuring and Describing Variables (Pollock) (pp.28-31)


Opportunities to discuss course content


Office Hours For the Week

  • When

    • Wednesday 11-1

    • Thursday 8-12

    • And by appointment


Course Learning Objectives

  • Students will learn the research methods commonly used in behavioral sciences and will be able to interpret and explain empirical data.

  • Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design. 


Variables


Turning things empirical

  • We experience it

  • We Define it

  • We give it value (operationalize)

  • We develop a hypothesis to explain/predict what we experienced in step 1


The Relationship Between them


How we measure our Variables

Units of Analysis


Units of analysis

  • The unit about which information is collected and that provides the basis of analysis

  • Each member of a population is an element

  • Why they are important?


Individual Unit

  • The lowest form of data

  • People, congressmen, presidents, etc


Aggregate Data

  • A collection of individual level units

  • Often measured in percentages

  • Footprints


The Poor over Time


Immigration over time


The Problem of Access


Fallacies made With Data


Ecological Fallacy

  • this arises when an aggregate/ecological level phenomenon is used to make inferences at the individual level.

  • Taking statewide data and applying to individuals

  • Does everyone in MS go to church?


The Exception Fallacy

  • taking one person's behavior, attributes, etc and applying it to an entire group

  • Using 1 example to define group behavior


Examples from Texas


Hypotheses


What Is a Hypothesis

  • An educated Guess

  • These are explicit Statements

  • They Try to explain a relationship

  • But they are only tentative until tested


The Null Hypothesis

  • The Statement of No Relationship

  • What we want to disprove

  • The Basic start of research

H0


Correlative Hypothesis

  • “there is a relationship between x and y”

  • A very weak statement


Positive Hypothesis

  • A directional hypothesis

  • “as the independent variable increases, the dependent variable increases”


Positive Relationship


Negative Relationship/Hypothesis

  • “As the independent variable increases, the dependent variable decreases”

  • Also called an inverse hypothesis


An Example


Logarithmic

  • Y=log(x)

  • The dependent variable changes rapidly, followed by less change


An Example


Curvilinear

  • The Relationship forms a curve!

  • The dependent variable increases to a point, and which point it begins to decrease


The Laffer Curve

  • The Debate over taxes

  • Ben Stein


Fuel Efficiency


Hulk Hogan

  • Roddy Piper (4:44)

  • King Kong Bundy (2:56)


More


Stating a hypothesis

There is a _____(direction)________relationship

between ________and ____________


Characteristics of good hypotheses


Good Hypotheses are Empirical

  • Something that we can Measure


Good Hypothesis are

Generalizable

Specific

Always State a direction

Always identify the iv and the d.v.

Avoid the correlative hypothesis

  • Apply to more than one case


Good Hypotheses are Plausible

  • There needs to be a Real world justification for why they are related

  • If Chewbacca lives on Endor, you must acquit


Good Hypotheses are Testable

  • You have to be able to test your hypothesisor it is just speculation.


Non-Tautological

  • Your independent and dependent variables are separate concepts


A Test of Scientific Knowledge

A Causal Hypothesis


What is a causal hypothesis?

  • The Boldest Hypothesis out there

  • A relationship that will occur 100% at all times, no exceptions

  • Difficult to Prove


To Prove a Causal Hypothesis

  • A Change in the Independent Variable will always cause a change in the dependent variable.

  • A change in X always precedes a change in Y

  • X is necessary and sufficient to cause a change in Y


Causality is the heart of scientific knowledge!


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