simply categorizes information, not typically numerical Example: marriage status, political party, gender, Football jersey number(no value, just a number to distinguish a person)
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Ordinal
Numbers used to place objects in order -Cannot assume that differences between values are equal Example: 1st, 2nd , ...
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Interval
Scale on which equal intervals between objects represent equal differences, but has no true zero Example: Fahrenheit
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Ratio
Equal intervals between objects ***Has a definite 0 Ex: hours you slept, weight, how many pets you have
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Types of Variables (list them)
Discrete vs Continuous Independent vs Dependent
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Discrete Variable
small set of possible values, if its a number its an integer(whole number) Ex: rolling a dice
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Continuous Variable
infinite number of possible values between the lowest and highest number on the scale Ex: length of time
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independent variable
The experimental factor that is manipulated by the researches; the variable whose effect is being studied
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dependent variable
The measurable effect, outcome, or response due to the independent variable
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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
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7 pitfalls when asking questions (list them)
Deliberate Bias Unintentional Bias Desire to Please Asking the Uniformed Unnecessary Complexity Ordering of Questions Confidentiality
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Deliberate Bias
wording a question to receive a desired answer
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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)
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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
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Asking the Uninformed
subjects may provide an answer to a question about which they have no knowledge
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unnecessary complexity
when a question isn't simple and easy to understand
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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)
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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
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Closed Question
a question in which the respondent is given a list to choose their answer from Ex: any multiple choice question
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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
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Reliability
a measure of the consistency of research results
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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
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Variability
unpredictable errors or discrepancies, a measure that is off the mark in any direction Ex: individual test scores vs the class average
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Natural Variability
variability that cannot be explained or predicted, that are due to nature Ex: individual pain tolerance
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Population(Parameter)
overall group of individuals that the researchers are interested in Ex: Ohio University Students
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Sampling Frame
a list of individuals from whom the sample is drawn Ex: Statistics Students
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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
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Margin of Error
the measure of accuracy of a sample survey(a percentage) 1/ (√ n)
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methods of sampling(list them)
Simple Random Stratified Random Cluster Systematic Random digit Dialing
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Simple Random Sampling
every member of the population has an equal chance of being selected for the sample
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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
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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
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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
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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
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Multistage Sampling
using a combination of sampling methods
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Population(Parameter) symbols
greek symbols: μ (mu) and σ (lower case sigma)
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σ(baby sigma)
population standard deviation
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μ(mu)
population mean
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Sample (Statistics) symbols
x̄ (x bar) s
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x̄ (x bar)
sample mean
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s
sample standard deviation
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Types of Data(list them)
Measurement vs Categorical Differences vs Relationships
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Measurement data
Quantitative data obtained by measuring objects or events(is a number) Ex: weight, speed, time
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Categorical Data
qualitative data representing the count of observations in each category "How many in a group of" Ex: a yes or no question