Methods Final

Descriptive Research

Describe nature of thing we are interested in

Easiest to conduct

Explanatory Research

Trying to find the cause behind the event

Hardest to conduct

Predicitive Research

predicting future events

Interviening research

focuses on effectiveness of something

Ethics

Doing what is morally and legally right when conducting scientific research

Research Question

statement answered through research process

is the ‘why’ of your study

Hypothesis

A statement describing the expected result or relationship between dependent and independent variables

Research Hypothesis

A statement of the expected relationship between the variables being analyzed in the current study

Null Hypothesis

A statement that the relationship or difference being tested does not exist

Rival Hypothesis

A statement offering an alternative explanation for the research findings

Theory

As an explanation that offers to classify, organize, explain, predict, or understand the occurrence of specific phenomena

Independent Variable

predictor variable

dependent variable

outcome variable being predicted by IV

Qualitative Research

examining various social settings and the individuals who inhabit these settings

Quantitative Research

Counting and measuring items associated with the phenomena in question

Structured Interview

No deviation from questions (quantitative)

Semi-strucutred interview

interviewer can go beyond basic questions

unstructured interview

Questions are constructed as you go

Full Participant

The researcher becomes a covert participant in the research

Participant Researcher

The researcher becomes a participant in the research, but is known to the study participants

Researcher who participates

The researcher observes study participants and is known among the participants

Complete Researcher

The researcher observes participants without their knowledge

Causality

Behaviors or events that LEAD to other behaviors or events

True Causal Relationship

Time ordering

Correlation

Control for Potential confounders

theoretical relationship

idiographic cause

numerous explanations for why an event occured

Nomothetic Cause

examination of relatively few observations to provide a partial explanation for an event

levels of measurement

nominal

ordinal

interval

ratio

Research Designs

Historical

Descriptive

Developmental/time series

case study

correlation

causal comparative

true experiment

quasi-experimental

Validity

measuring what it claims to measure

face validity

questions are believed to be measuring some concept or construct

content validity

whether the items or questions are representative of possible items c

criterion validity

whether the scores of the new instrument relate to some external standard

construct validity

whether items measure what they intend to

Reliability

over time, questionnaire yields consistent results

Stability

respondents provide same answers at a later point in time

Consistency

questions are strongly related and measure the same concept

Principle of Unidimensionality

Holds that items making up the scale need to represent one dimension befitting a continuum that is supposed to be reflective of only one concept

3 things required for probability sampling

• All members of a given population have the same chance of being selected

• Selection of each member is independent from the selection of any other member

• Selection occurs without replacement

4 types of probability sampling

simple random

stratified random

systematic random

cluster

4 types of non-probabiity sampling

purposive

quota

snowball

convenient

Confidence interval

range of numbers in a normal distribution within which our estimated population parameters fall

Confidence level

estimated probability that our population will fall within a given confidence interval

Survey data collection

• mail surveys

• self administered

• interviews

• telephone survey

Data coding

Assigning values to the data for statistical analyses

Univariate Data Analysis

Involves examining the characteristics/attributes of one variable at a time (Descriptive statistics)

Bivariate Data Analysis

Involves examining the relationship between two variables (both comparative and inferential)

Multivariate Data Analysis

Involves examining the relationship between three or more variables (both comparative and inferential)

Absolute frequency distribution

Displays data based on the assigned numbers per category

Relative Frequency Distribution

Displays percentage breakdown of each category as a percentage of the total

Cumulative frequency distribution

every subsequent category is added to the previous value, creating a cumulative total

Cumulative relative frequency distribution

Every subsequent percentage breakdown of each category is added to the previous percentage breakdown, creating a cumulative percentage totalR

Range (Variability)

differences between lowest and highest scores

Standard Deviation (variability)

the distance a score in a distribution is from the meal

Variance (variability)

the standard deviation squared

Leptikurtic

Peaked

Platikurtic

Flat

Measures of association

Pearson’s’ r

Phi Coefficient

Rho

point biserial

polyserial

polychloric

tetreachloric

Crime Rate equation

Percentage Change Equation

Inferential Statistical Tests

contingency tables

t-tests

correlation

ANOVAs

bivariate regression

multivariate regression