psychology chapter 2: methods in psych notes
psychology chapter 2: methods in psych notes Psy120000
Purdue University Calumet
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This 3 page Class Notes was uploaded by Kira Lisle on Thursday October 13, 2016. The Class Notes belongs to Psy120000 at Purdue University Calumet taught by Mrs. January in Fall 2016. Since its upload, it has received 21 views. For similar materials see Elementary Psychology in Educational Psychology at Purdue University Calumet.
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Date Created: 10/13/16
Chapter 2: Methods of Psych ❖ How do we know? ➢ Intuition ➢ Common sense ➢ Someone tells us ➢ We see it ourselves ➢ Experience ➢ Evidence ❖ Problems with intuition ➢ Hindsight Bias > we tend to believe, after learning an outcome, that we would have foreseen it. The “I-knew-it-all-along” phenomenon ➢ Overconfidence > we tend to think we know more than we do. Confirmation bias. ➢ False consensus effect > tendency to overestimate the extent to which others share our beliefs and behaviors. Happens a lot with sports ➢ Illusory correlation perception of a relationship where none exists ■ A gambler who had sat at the same slot machine all day is hesitant to leave because he feels that at this point his chances of winning are better. ❖ The Scientific Method ➢ Scientific method: set of principles about the appropriate relationship between ideas and evidence ➢ Empiricism: belief that accurate knowledge can be acquired through observation; essential element in scientific method ➢ Empirical method: set of rules and techniques for observation ❖ Empiricism > how to know things? ➢ Theory: hypothetical explanation of a natural phenomenon ➢ Rule of Parsimony: s implest theory that explains all the evidence is the best one ➢ Hypothesis: falsifiable prediction made by a theory ❖ The challenge of studying human behavior ➢ People are difficult to study ■ Complexity ■ Variability ■ Reactivity ➢ Psychologists use both ■ Methods of observation ■ Methods of explanation ❖ Methods of observation ➢ Observe: use one’s senses to learn about the properties of an even or an object ❖ Measurement: defining and detecting ➢ Measurement requires defining the property to be measured and finding a way to detect it ➢ Operational: description of a property in concrete, measurable terms Define the property Detect the property Generate an operational definition that Design an instrument that has has validity rehability and power ❖ Measurement: defining ➢ Happiness > frequency of smiles ➢ Intelligence > ability to solve increasingly complex problems ➢ Shyness > discomfort in social situations ■ Clinginess to familiar person, or object ■ Avoids interacting with new people ❖ Measurement: detecting ➢ Measure: device that can detect the condition to which an operational definition refers ■ Validity: extent to which a measurement and a property are conceptually related ■ Reliability: tendency for a measure to produce the same measurement whenever it is used to measure the same thing ■ Power: ability of a measure to detect the concrete conditions specified in the operational definition ➢ People act differently when they know they are being watched ➢ You must be valid to be reliable ❖ Demand characteristics: those aspects of an observational settings that cause people to behave as they should ➢ People rarely admit to being prejudiced when asked, and they generally won’t behave in prejudiced ways if someone is watching ❖ Demand characteristics and observer bias ➢ Naturalistic observation: technique for gathering scientific information by unobtrusively observing people in their natural environments ➢ Observer bias: expectations can influence observations and influence perceptions of reality ➢ Double-blind: observation whose true purpose is hidden from both the observer and the person being observed ❖ People’s expectation can cause the phenomena they expect ➢ Frequency distribution: graphical representation of measurements arranged by the number of times each measurement was made ❖ Descriptions and graphic representations ➢ Graphic representations describe data ■ Normal distribution: mathematically defined frequency distribution in which most measurements are concentrated around the middle ■ Skewed distribution: non-normal (positive or negative skewed) ❖ Descriptive statistics ➢ Two kinds of descriptive statistics ■ Descriptive statistics are used to describe two important features of a frequency distribution: central tendency (where do most of the scores lie?) and variability (how much do the scores differ from one another?) ➢ Descriptive statistics are brief summary statements about a frequency distribution ■ Central tendency (center or midpoint) ■ Mode: value of the most frequently observed measurements ■ Mean: average value of all the measurements ■ Median: value that is in the middle ➢ Variability (extent measurements differ) ■ Range: v alue of the largest measurement in a frequency distribution minus the value of the smallest measurement ■ Standard deviation: statistic that describes the average difference between the measurements in a frequency distribution and the mean of that distribution ➢ Variable: property whose value can vary across individuals or over time ❖ Correlation ➢ Two variables are said to be correlated when variations in the value of one variable are synchronized with variations in the value of the other ■ Positive correlation > both go up or both go down ■ Negative correlation > one goes up as the other goes down (they go in opposite directions) ❖ Correlation coefficient: easure of the direction and strength of a correlation ® ➢ R ranges ■ -1 (perfect negative correlation) ■ +1 (perfect positive correlation) ■ 0 (as no correlation)
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