Lecture5-Jan+19th-Measuring+variables

# Lecture5-Jan+19th-Measuring+variables -

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Unformatted text preview:   Tutorial/quiz 3 due TODAY    Thursday = Tutorial/Quiz 4    Grades for Quiz 2 are not showing up!    Exercise 2 will be posted today after class.    New due date is TUESDAY Jan 26th    NEXT WEEK    EXAM 1 coming up!!!!!!    Review session times will be communicated  next lecture    ONLINE Review session    WHAT TO EXPECT ON EXAM?    50 MC questions (5 pts each)    HOW DO I DO WELL ON TEST?    Come to class    Review lecture notes    Go over book descriptions of concepts covered in  class    Generating Hypothesis    Characteristics of Hypotheses    Deﬁning variables    Setting up a study    Research hypothesis = Testable  prediction    Speciﬁc    Falsiﬁable    Characteristics of hypotheses:    Descriptive vs. Causal    Directional vs. Non‐directional    Choice of directional vs. non‐directional depends on  previous research, theory etc.    Variable: two or more levels of a  characteristic, event, trait, etc…    Operational deﬁnition    Deﬁnition of procedure used by research to  measure or manipulate variable    Operational deﬁnition    Deﬁnition of procedure used by research to  measure or manipulate variable    Some variables are easier to quantify that others  ▪  Memory vs. Extraversion    As long as something is numerically qualiﬁed, it can  be measured!  ▪  Diﬀerent ways of doing it…we’ll discuss it later…    Descriptive (Describe)    Correlational (Predict)    Experimental (Explain)    What is the main diﬀerent among the three?    Level of control exerted by researcher     Why only experimental method allows for  cause and eﬀect conclusions?    Direct manipulation of variables!!!  Independent vs Dependent Variables    Independent Variable (IV) = Manipulated or  Causal Variable    Dependent Variable (DV) = aﬀected or  outcome variable      True IV=manipulated  experiment    Not true IV=not manipulated  quasi‐ experiment    participant variable (e.g., gender, age,  etc.)    Study descriptions will be provided.    You’ll need to identify:    IVs and their level (true IV or not?)    DVs    Operational deﬁnitions    Generating Hypothesis    Descriptive vs. causal    Directional vs. non‐directional    Identifying and deﬁning variables    Setting up a study    Choosing study type    Choosing measures    Choosing participants    Depends on the characteristics of our  hypothesis!    Descriptive: Formal statement of a predicted  observation  ▪  Correlational    Causal: Explains possible cause for the  pattern stated in the descriptive hypothesis.   ▪  Experimental  Allow us to study:    Are two things related to each other?    What is the direction of the association?    What is the strength of the association?    Relationship is measured by a correlation  coeﬃcient    Descriptive Hypotheses    Non‐directional  ▪  There is a relationship between age and amount of veggie  eaten in a week    Directional  ▪  As children grow, they eat more veggies    Existence  Age    Direction  Age  Amount of veggies  Age  Amount of veggies  Amount of veggies    Strength  Strong  Correlation  moderate  Correlation    Correlation coeﬃcient     Is represented by r    Ranges from –1 to 1    Allow us to answer:    Are two things related to each other?    What is the direction of the association?    What is the strength of the association?    Are two things related to each other?    If  r = 0 : no    If  r ≠ 0 : yes    What is the direction of the association?    If –1 < r < 0 : negative correlation    If  1 > r > 0 : positive correlation    What is the strength of the association?    As r gets close to zero the correlation gets weaker    As r gets close to  1  the correlation gets stronger  •  Direction of causation is unknown  •  Possible third variable    Spurious correlation    Depends on the characteristics of our  hypothesis!    Descriptive  ▪  Correlational    Causal: Explains possible cause for the  pattern stated in the descriptive  hypothesis.   ▪  Experimental    Hypothesis    Children who know that veggies are healthy will  choose them to a greater extent compared to  children without that knowledge  ▪  Directional hypothesis    Experiment    Manipulation            Eﬀect    Experiment    Manipulation            Eﬀect  Knowledge  Type of video watched:  informative vs. not  Choice  Choosing broccoli over  crackers  Independent   variable  Type of video watched:  info or no info  Experimental  group  Control  group    How are we sure that any potential eﬀect is  due to our IV?    We need to ensure that the only diﬀerence b/w  the “experimental” and “control” group is  exposure to our manipulation!    Random assignment    Ensures each participant has SAME probability to  be in either group    Ensures that any diﬀerence is averaged out!    Choosing study type    Type of study depends on type of hypothesis we  are interested in testing  ▪  Descriptive = Correlational study  ▪  Causal = Experimental study    Generating Hypothesis    Descriptive vs. causal    Directional vs. non‐directional    Identifying and deﬁning variables    Setting up a study    Choosing study type    Choosing measures    Choosing participants    How do we measure variables?    Measurement Types    Measurement scales    Decide of the measurement type    Behavioral    Physiological    Self‐report    Test    How do we measure variables?    Measurement Types    Measurement scales    Nominal Scale    Numbers represent groups    Label categories  Examples    Performance on exam  ▪  Pass=1  ▪  Fail=0    Gender  ▪  Females=999  ▪  Males=777    Ethnicity  ▪  ▪  ▪  ▪  Caucasian=1  African‐American=2  Asian‐American=3  Other=4    Ordinal Scale    Meaningfully ordered    Know which is greater    Do not know how much  greater  Examples    Self‐Esteem  ▪  Low=1  ▪  Med=2  ▪  High=3    Reading group  ▪  Low  ▪  Med  ▪  High    Ranking participants  from worst to best    Interval Scale    Numeric values represent equal distance    No true zero point=> values can be negative    Ratio Scale    Absolute zero    Relative magnitude  3’ 4’ 7’ 12’ 1=“short” Nominal 14’ 24’ 2=“tall” Ordinal 1 2 3 4 5 6 Interval 0 1 4 9 11 21 Ratio 3 4 7 12 14 24   Depends on your question    Do two group diﬀer?  Nominal   Does one group have more?  Ordinal   How much more?  Interval   Three times as much?  Ratio   Depends on your planned statistical analyses    Nominal and ordinal data => nonparametric  statistical tests     Interval and ratio data => parametric statistical  tests      Likert Scales    Are actually NOMINAL scales    In practice used as interval scales  Strongly Moderately Slightly Neutral Slightly disagree disagree disagree agree 1 2 3 4 5 Moderately Strongly agree agree 6 7   Climate  IV    Ego‐oriented    Task oriented  IV levels    Persistence in task completion  DV    Number of attempts at completing tasks  Behavioral  measure/  Ratio scale  Operational  deﬁnition of  DV  ...
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## This note was uploaded on 06/21/2011 for the course PSYCHOLOGY Psych 41 taught by Professor Castelli during the Winter '10 term at UC Davis.

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