simply categorizes information, not typically numerical
Example: marriage status, political party, gender, Football jersey number(no value, just a number to distinguish a person)
Ordinal
Numbers used to place objects in order
-Cannot assume that differences between values are equal
Example: 1st, 2nd , ...
Interval
Scale on which equal intervals between objects represent equal differences, but has no true zero
Example: Fahrenheit
Ratio
Equal intervals between objects
***Has a definite 0
Ex: hours you slept, weight, how many pets you have
Types of Variables (list them)
Discrete vs Continuous
Independent vs Dependent
Discrete Variable
small set of possible values, if its a number its an integer(whole number)
Ex: rolling a dice
Continuous Variable
infinite number of possible values between the lowest and highest number on the scale
Ex: length of time
independent variable
The experimental factor that is manipulated by the researches; the variable whose effect is being studied
dependent variable
The measurable effect, outcome, or response due to the independent variable
Seven Critical Components to a Good News Report(words to remember, list them)
-Source and funding
-Researchers contact
-Individuals selected
-Measurements and questions
-Setting
-Extraneous differences
-Magnitude/effect
7 pitfalls when asking questions (list them)
Deliberate Bias
Unintentional Bias
Desire to Please
Asking the Uniformed
Unnecessary Complexity
Ordering of Questions
Confidentiality
Deliberate Bias
wording a question to receive a desired answer
unintentional bias
wording a question in a way that might be misinterpreted by the respondent
Ex: Do you take drugs? (meant prescribed or over the counter medicine)
Desire to please
Respondents have a desire to please the person who is asking the question. Tend to understate response to an undesirable social habit/opinion
Ex: "do you floss regularly?" No one does lets be real, but most people tell the dentist they do
Asking the Uninformed
subjects may provide an answer to a question about which they have no knowledge
unnecessary complexity
when a question isn't simple and easy to understand
Ordering of Questions
The order in which questions are presented can change the results (especially if one question gives more insight on another question asked)
Confidentiality
people answer questions differently depending on how anonymous they believe they are
Ex: if you ask someone if they drink underage, might say no to avoid getting in trouble or being judged
Closed Question
a question in which the respondent is given a list to choose their answer from
Ex: any multiple choice question
Open Question
A question the respondent is allowed to answer with their own words
Ex: short response, essay
a measure of accuracy, does the research measure what it's supposed to
Reliability
a measure of the consistency of research results
Bias
a measure that is consistently off the mark in ONE direction
Ex: bathroom scale tells you you're 145, 146, 147, you're actually 140
Variability
unpredictable errors or discrepancies, a measure that is off the mark in any direction
Ex: individual test scores vs the class average
Natural Variability
variability that cannot be explained or predicted, that are due to nature
Ex: individual pain tolerance
Population(Parameter)
overall group of individuals that the researchers are interested in
Ex: Ohio University Students
Sampling Frame
a list of individuals from whom the sample is drawn
Ex: Statistics Students
Sample survey(Statistics)
a subset of the population and sampling frame from which the researches are going to study
Ex: Dr. McCartheys 12:30 statistics class of students
Margin of Error
the measure of accuracy of a sample survey(a percentage)
1/ (√ n)
methods of sampling(list them)
Simple Random
Stratified Random
Cluster
Systematic
Random digit Dialing
Simple Random Sampling
every member of the population has an equal chance of being selected for the sample
stratified random sampling
Dividing the population into groups and then taking a sample from each group
Ex: East, South, West green, take 10 residents from each green
cluster sampling
Divide the population into groups or 'clusters'
Select a random amount of groups
Use all members of the selected groups/clusters
Ex: Take 2 specific dorm halls, interview everyone in those 2 halls
systematic sampling
select some starting point and then select every kth element in the population
Ex: put participants in a line, choose every 4th person
random digit dialing
a polling method in which respondents are selected at random from a list of 10-digit telephone numbers, with every effort made to avoid bias in the construction of the sample
Multistage Sampling
using a combination of sampling methods
Population(Parameter) symbols
greek symbols: μ (mu) and σ (lower case sigma)
σ(baby sigma)
population standard deviation
μ(mu)
population mean
Sample (Statistics) symbols
x̄ (x bar)
s
x̄ (x bar)
sample mean
s
sample standard deviation
Types of Data(list them)
Measurement vs Categorical
Differences vs Relationships
Measurement data
Quantitative data obtained by measuring objects or events(is a number)
Ex: weight, speed, time
Categorical Data
qualitative data representing the count of observations in each category
"How many in a group of"
Ex: a yes or no question