ANTH 260 Introduction to Physical Anthropology LAB Week 2 Lab Instructor/TA: Zach Garfield Washington State University Vancouver Spring 2015
A closer look at variables What s a variable? Qualitative (Discrete/Categorical) vs. Quantitative (Continuous) Qualitative variables: Binary vs Ordinal - Example: Binary = Sex, Ordinal = Likert Scale (Strongly disagree, Disagree, etc.) - Research designs specify an independent variable and a dependent variable Independent variable (IV): the variable being manipulated or changed Dependent variable (DV): the variable being measured In your model, IVs impact DVs
IVs & DVs Examples: - People who drive cars get better gas mileage on average than people who drive trucks. - IV = type of vehicle (car or truck) DV = gas mileage (miles per gallon) Students with better grades will be more likely to get jobs after graduating. IV = Grades (GPA) DV = Occupational status (Job: yes or no)
3 general types of knowledge Descriptive knowledge Predictive knowledge (Causal) Understanding
Descriptive knowledge Describing phenomena by defining, classifying, and/or measuring them Often includes separating, discriminating, or distinguishing between similar behaviors Example: Monkeys have tails
Predictive knowledge Knowing how to use a measure of one variable to predict the measure of another Requires an established pattern of relationship Just because there is a relationship, doesn t mean one variable (necessarily) causes the other Examples: Nutritional status (quality of diet) impacts bone growth during adolescence.
Causal/Understanding Knowing which behaviors have a causal relationship Knowing what the causal variable is allows you to manipulate the variable and produce a change in a second variable Example: Excessive UV exposure causes skin burn Causal findings only come from true experiments!!!
3 kinds of hypothesis Related to 3 types of knowledge Attributive Associative Causal
Attributive hypotheses A phenomenon exists, can be measured, and can be distinguished from other similar phenomenon One variable Example: There is one living member of the genus Homo in the world today - - Supporting evidence: Documentation of one, and only one, Homo species Contrary evidence: Documentation of some other Homo species
Associative hypotheses States that a relationship exists between two variables Knowing the amount or type of one variable helps you predict the amount or type of another variable Two variables (bivariate relationships) - Positive relationship - as one variable increases (or decreases), another variable also increases (or decreases); variables change in the same direction (+/+), (-/-) - Negative relationship - as one variable increases, another variable decreases (and vise versa); variables change in opposite directions (+/-), (-/+) Evidence: Significant or non-significant statistical calculations Example: Greater attendance to lectures (IV) will be positively related to scores on exams (DV)
Associative hypotheses
Causal hypotheses States that differences in amount or kind of one variables causes/ produces/creates/changes/etc., differences in amount or kind of one variable Two variables (bivariate) - causal variable (IV), effect variable (DV) Evidence needed to support causal hypothesis - True experimental design Random sample & random assignment (with control group) & manipulation of the IV - Temporal precedence (cause before effect) - Statistical significance - Elimination of alternative explanations Example: Exposure to violent media will cause an increase in violent reactions in social settings
Hypotheses & knowledge Attributive hypotheses Descriptive knowledge Associative hypotheses Predictive knowledge Causal hypotheses Causal/Understanding
Psychosocial variables Humans have an evolutionary history of sociality Social environmental influences, social environmental reactions Definition: pertaining to the interaction between social and psychological factors Measurable variable of some trait/state related to an emotional or behavioral condition in a social context Examples: social status, time pressure, social support, security, autonomy, locus of control, self-esteem, etc
Biomarkers A measurable substance in an organism, which when present is indicative of some phenomenon (e.g. disease, infection, environmental exposure) Invasive and non-invasive detection methods Detectable following external stimulus
A closer look at cortisol Component of the HPA Axis - Hypothalamic-pituitary-adrenal axis - Part of neuroendocrine system (brain-hormones) Primary function of cortisol: metabolization of energy Stress hormone, but overly associated with the stress response Complex functions
Cortisol cont. Diurnal variation (highest levels after waking, lowest levels in the evening) - CAR (cortisol awakening response): the change in cortisol concentration that occurs during the first hour after waking from sleeping Released in response to a variety of stimuli (stressors, etc) Rapid response release Can measure in blood or saliva Implicated in many psychosocial measures
Meta-analysis Chida & Steptoe, 2009 147 studies from 62 articles Psychosocial variable categories: job stress, general life stress, depression, anxiety, fatigue, PTSS, positive states CAR: positively associated with job stress, general life stress; negatively associated with fatigue
Results of our lit search Discuss your articles in your groups Focus on research question & type of hypothesis Identify focus population Identify variables: IVs and DVs Are there any themes to your groups articles? Summary chart: http://goo.gl/yocc04
Study 1: Relationship between cortisol & psychosocial variable Biomarker variable = Salivary cortisol, CAR??? Psychosocial variable? Focus population? - How do we expect participants to vary? Research question / Hypothesis? - What relationship do we expect to see between some variable(s) and cortisol? Assignment: Come up with 2 ideas for our study - Focus on questions above - What two variables??? What can we compare??? - Use summary chart to help with ideas: findings, variables, etc.