Chapter 1+2 Flashcards
What is cross-sectional research
Research done at one time about a specific group
What is experimental research
Experiments done to find an explanation
Longitudinal research
Done over a long period f time (years) to identify a trend
Quantitate Research
All research put into numbers and tweaked from there
Data
Scores on info expressed as numbers
Variables and example
Traits that change values case by case
Ex: family size
Cases and why its based on
Entities from which data is gathered
Usually based on people sometimes cities
Find the data, variables, and cases
The average student debt is $26,500
Variable: amount if debt
Data: $26,5000
Case: recent university grads
2 basic kinds of statistical techniques
Descriptive
Inferential
Types of descriptive statistics
Univariate
Bivariate
Multivariate
Univariate
1 variable
%, rates, averages, graphs
Bivariate and example
2 variables
Measures of association, scatterplots
Ex: are unemployment and crime rates related
Multivariate
More than 2 variables
Multiple regression, partial correlation
Estimation
Using statistical information from a sample to estimate characteristics of a population
Hypothesis testing
Using statistical information from a sample of test a hypothesis an out the population
Observational phase circle
Social research process
Independent dependent variable chart
Discrete variables
Variables in units that can’t be subdivided (# of people living in a house)
Continuous variables
Variables in a unit that can be subdivided (income)
3 level of measurement
Nominal
Ordinal
Interval-ratio
Nominal variables must be
Homogenous (include similar cases as one)
Exhaustive (a catergory for everyone)
Mutually Exclusive
Ordinal variables
Measuring opinions and attitudes
Ex: on a scale how good is your health
(no numbers)
Excellent
Good
Bad
Interval-Ratio variables
Distance between scores is equal
Uses numbers
Ex: number of people in a household
Frequency distribution
The distribution of a variables values by reporting the number of times each score of a variable occurred
proportion
of cases in a response category divided by the # of cases in all categories
rates
of actual occurrences divided by the # of possible occurrences
frequency distribution
table that displays the number of cases in each response category of a variable
stated limits
interval of a frequency distribution when stated as a discrete response category
real limits
interval of a frequency distribution when stated a continuous response category
Statistics
Mathematical techniques for organizing and analyzing data
Theory
Generalized explanation of the relationship between two variables
Descriptive statistics
Summarizes the distribution of a single variable or measuring the relationship between variables
Data reduction
Summarizing scores with few statistics
Response categories
A variables possible attributes, qualities, or characteristics
