ANTH 260 Introduction to Physical Anthropology LAB

Transcription

1 ANTH 260 Introduction to Physical Anthropology LAB Week 2 Lab Instructor/TA: Zach Garfield Washington State University Vancouver Spring 2015

2 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

3 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)

4 3 general types of knowledge Descriptive knowledge Predictive knowledge (Causal) Understanding

5 Descriptive knowledge Describing phenomena by defining, classifying, and/or measuring them Often includes separating, discriminating, or distinguishing between similar behaviors Example: Monkeys have tails

6 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.

7 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!!!

8 3 kinds of hypothesis Related to 3 types of knowledge Attributive Associative Causal

9 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

10 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)

11 Associative hypotheses

12 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

13 Hypotheses & knowledge Attributive hypotheses Descriptive knowledge Associative hypotheses Predictive knowledge Causal hypotheses Causal/Understanding

14 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

15 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

16 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

17 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

18 Meta-analysis Chida & Steptoe, 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

19 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:

20 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.