Com 304 Exam 1

Front 1

The Scientific Method

Back 1

Gives basics of collecting, interpreting, and sharing data in a common manner

Set of rules and procedures that use to collect research

Front 2

Scientific Method Requirements/overview (7)

Back 2

Empirical (systematic observation)
Objective and unbiased
Collection and analysis of data
Conclusions
Share Data
Replicate
Falsifiable: can be proven

Front 3

Values

Back 3

Arguement and statement

Front 4

Facts

Back 4

Proven

Front 5

Constructs

Back 5

hypothetical concepts, must define it further in order to study because it cannot actually be seen
(3 PARTS)

Front 6

Constructs (3 parts)

Back 6

Label
Conceptual Definition
Operational Definition

Front 7

Constructs:
Conceptional Definition

Back 7

-translates concept into understandable message
-hone in and define specifically
-not a dictionary definition
-high self esteem might be conceptually defined as a person demonstrating a high degree of self worth.

Front 8

Constructs:
Operational Definition

Back 8

-Measurable characteristics, observable

- high self esteem might be operationally defined as scoring above a certain number of a self-esteem scale.

-Adequate, accurate, clear

Front 9

Theories

Back 9

Purpose is to predict and explain

Interrelated and combined constructs

If you can predict, you can control

used to fit together constructs/variables, predict, relate to other theories

Front 10

Humor is a __________
while explaining why people are funny is a _________

Back 10

construct
Theory

Front 11

What are variables

Back 11

2 or more categories

Front 12

Independent Variables

Back 12

Variable that causes (A)
A causes B

Front 13

Dependent Variable

Back 13

Variable that will be changed, typically variable that is measured

B

Front 14

Categorical Variable

Back 14

-non-numeric characteristics
-order is irrelevant
-ex: major, sex, political party, membership
-use a nominal scale

Front 15

Quantitative Variable

Back 15

-Measured numerically
-ex: gpa, age, scales, sat

Front 16

Nominal Measurement

Back 16

Categorical variables

name/label of category

number ranking doesn't matter

Front 17

Ordinal Measurement

Back 17

Quantitative

Rank from high to low

Order measured

Not completely informative because difference isn't measured, just ranking, so you may not know how close variables really are

Front 18

Interval Measurement

Back 18

Quantitative

Differences are meaningful

No natural zero starting point ex: a zero rating doesn't mean lack of variable, like 0 degrees doesn't mean no temperature

Similar to ordinal but the differences matter

Front 19

Hypothesis (& 2 types)

Back 19

Prediction about the relationship of 2 or more variables

Specific and falsafiable

Comparison or Relational

Front 20

Comparison Hypothesis

Back 20

How a categorical variable compares with a second variable (can be categorical or quantitative)

ex: how male and females differ in life expectancy

Front 21

Relational Hypothesis

Back 21

How 2 quantitative variables are related or associated

ex: shyness and self esteem interval scales

Front 22

Directional Hypothesis vs Non directional Hypothesis

Back 22

Directional: show a direction, positive negative, up down, increase decrease, more less *One Tail
ex: amount of time studying positively associated with grade

Non-Directional: doesn't specify direction *Two Tail
ex: grades are associated with speeches

Front 23

Population

Back 23

Entire group of people that share one or more characteristic

Generalize Results

Size depends on definition- varies

Set of individuals in a particular situation

Front 24

Parameter

Back 24

Numerical representation of the POPULATION

46% of undergrads believe...

Front 25

Sample

Back 25

Vary in size

select smaller, more manageable sample from the population

Intent is to generalize the population

Front 26

What % of Purdue Undergrads believe War is wrong? You ask 400 students

What is the
population
sample

Back 26

Population: purdue students
Sample : 400 students

Front 27

Statistic

Back 27

Numerical representation of the SAMPLE

48% OF 400 purdue students believe...

Front 28

Sampling Error

Back 28

Samples are only representative of the popuation, not perfectly accurate

Front 29

Non Sampling Error

Back 29

Human Error
Researcher Mistake

Front 30

Random Sampling

Back 30

Members of population are selected so each person has an equal chance of being selected

Front 31

Nonrandom Sampling:

Back 31

Individuals do not have equal chance of being selected

Front 32

Nonrandom Sampling:
Systematic

Back 32

Every 4th person
stick with pattern

Front 33

Nonrandom Sampling:
Convenience

Back 33

Using convenient sample

Like Purdue using students for data

Front 34

Nonrandom Sampling:
Stratified

Back 34

2 sub groups and draw samples

male and female

Front 35

Nonrandom Sampling:
cluster

Back 35

divide population into sections, randomly select from clusters