What are the three claims?? 1. frequency - make a
statement about variable or about relationships between variables - something that varies, it must have at least two levels (values) What is a constant variable? - something that could potentially vary but that has only one level in the study in question (IV) What is a manipulated variable? - we control its levels by assigning participants to the varying levels of the variable
- researchers record an observation, statement or value Variables can be described in what two ways? 1. Conceptual definition What is a conceptual definition of a variable? - when researchers discuss theory or journalists write about research....(abstract concepts) What is an operational definition of a variable? - when one turns a concept of interest not a measured or manipulated variable....needed for testing hypotheses via empirical research Give a run through example of both variable definitions. 1. conceptual definition: weight gain How are variables commonly stated as definition wise? - conceptually Describe what a frequency claim is! - describe a rate or level of something Frequency Claims only focus on how many variables? Measured or Manipulated? - only one variable Are Anecdotal claims frequency claims? NO What is an Association claim? - argues that one level of a variable is LIKELY to be ASSOCIATED with a particular lvl of another variable Association claims involve how many variables?Measured , manipulated? at least two What are used to see if two variables are related after measuring variables for an association claim? What are the four types of Association Claims? 1. positive associations Explain what a Positive Association is! - aka + correlation Explain what a Negative Association is! - aka - correlation or inverse association Explain Zero association claims! - no association btwn the variables Explain Curvilinear Association claims! - the level of one variable changes its pattern as the other variable increases. What is a prediction in regards to association claims. - mathematically looking to the future...aka using an association to make our estimates more accurate. Predictions and + /- associations? - if we know the level of one variable we can more accurately guess or predict the level of the other variable. Are predictions from association claims perfect? - no usually they are off via certain margin When it comes to association claims and predictions, what makes them stronger/more accurate? - if there is a strong
relationship btwn two variables = more accurate prediction With predicting association claims (+/-) if we know absolutely nothing about an association what will our predictions be based on? Associations help us make predictions by reducing what? the size of our prediction error Can Zero association claims help us make predictions? - NO Explain what a causal claim is! -
argue that one of the variables is responsible for CHANGING the either What are the three steps to go from an association claim to a causal one? 1. establish two variables are correlated (cannot have a zero relationship.....the cause variable and the outcome v) What are the four big validities? 1. Construct - reasonable, accurate and justifiable What two validates apply to interrogating frequency claims? - Construct and External validity Frequency Claim: - how well did they measure their variables Frequency Claim: - how well the results of the study generalize to or represent people
and contexts besides those in the study itself! What are the three types of validity that apply to interrogating Association Claims? 1. Construct Association Claim: -assess each variable Association Claim: - can the association generalize to other populations? other contexts, times, places? Association Claim: - statistics are sued to describe data and estimate the probability that results can or
cannot be attributed to chance Association Claim: 1. Type I Errors: based on results concluding there is an association btwn 2
variables when there is none. (false alarm) - As "A" changes, "B" changes What are the three rules for Causation? 1. Covariance How do researchers attempt to support a causal claim? - experiment! How do experiments provide temporal precedence and internal validity for causal claims? - by manipulating one variable and measuring the other one can ensure that by manipulating the causal variable it came first.
Causal Claims: 1. Causal Claims: 1. do the results generalize? What validity is important for frequency claims?External validity is extremely important with frequency claims — studies that conclude how frequent or common something is. For example, “14% of College Students Consider Suicide” is a frequency claim.
What does one need to consider when interrogating frequency claims?To interrogate a frequency claim, ask questions about the study's construct validity (quality of the measurements), external validity (generalizability to a larger population), & statistical validity (degree of error in the percentage estimate).
How do you evaluate a frequency claim?The best way to identify frequency claims is that they focus on only one variable—such as frequency of worrying, rate of smiling, or amount of texting. In addition, in studies that support frequency claims, the variables are always measured, not manipulated.
How do you know if a frequency association and causal claims are valid?The best way to distinguish frequency claims from the other two types of claims (association and causal claims) is that they focus on only one variable— such as depression, happiness, or rate of exercise. Another distinguishing feature is that in frequency claims, the variables are always measured, not manipulated.
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