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Exam 1 study guide

by: Brenna Eisenberg

Exam 1 study guide PSY 313

Brenna Eisenberg
GPA 3.535

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About this Document

Notes covering all of the material for exam 1. be sure to also study the practice questions on blackboard.
Intro. To Research Methodology
B. Seymour
Study Guide
Science, Psychology, Research Methodologies, research, surveys, Study Guide, Exam 1, Theory, Sampling, notes
50 ?




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This 4 page Study Guide was uploaded by Brenna Eisenberg on Wednesday October 5, 2016. The Study Guide belongs to PSY 313 at Syracuse University taught by B. Seymour in Fall 2016. Since its upload, it has received 25 views. For similar materials see Intro. To Research Methodology in Psychology (PSYC) at Syracuse University.


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Date Created: 10/05/16
Exam 1 study guide Wednesday, October 5, 201612:42 PM • Method of tenacity- hold something to be true because it has been around for a while. Ex- elephantsare afraid of mice • Good research ideas are testable, logical and refutable • Science is: ○ Empirical- driven by evidence and observation. ○ Public- write papers, attend conferences, distributeto popular media. ○ Objective, not subjective- recognize and avoid bias with statistics, replication, and collaboration. • Theory- an idea about how the world works based on empirical data. Explanation of how scientific laws fit together. Describes how constructs are related • Construct- The concept(s) of interest. Not directly observable. Ex- stress, attention,love, memory, knowledge. • Hypothesis- specific idea about the relation between constructs that is derived from the theory. Ex- stress reduces concentration ○ To test hypothesis, constructs must be defined • Operational definition-specifies how each construct will be measured. Turns constructs into something measurable and observable. ○ Ex- measure heart rate in relation to stress • Types of research: ○ Descriptive- gives a snapshot of the world. Not concerned with relationships between variables, but a description of the variables themselves. Ex-how many people drive drunk on college campuses? ○ Correlational- how are two variables related. Ex- do people who sleep longer have better memory? Does not mean causation ○ Experimental research- establishes a cause and effect relationship between two or more variables.  Does sleeping longer lead to better memory?  Tests a hypothesis  Has constructs, operational definitions, IVs, and DVs. • Independentvariable- what you manipulate. What goes into the experiment • Dependentvariable- what you measure • Variables- measure attributes that vary. ○ Heart rate, height, reaction time • Observational study- watching and recording data about behavior • Quantitative- amount, number of things, frequency, numerical • Qualitative- type of things, description, themes • Data collection: ○ What-  behavior categories. Identify every category of behavior before observation. List everything that qualifies as a member of each category, need clear operational definitions. ○ When-  Frequency method- count number of times you observe behavior in a fixed amount of time. Better for discrete variables  Duration method- measure amount of time spent engaging in behavior. Better for continuous variables.  Interval method- set time intervals and note if behavior is observed during that time. Yes or no. ○ How-  Event sampling- observe behavior 1/ observe behavior 2  Individual sampling- all behaviors from person 1/ or from person 2  Time sampling- observe, record, observe, record • Naturalistic observation- try not to disturb the subjects being observed. Hide, habituate. Not part of the experiment. ○ Jane Goodall- lived in Tanzania with chimps, observed their behaviors. Discovered things through pure observation, took careful notes. • Participant- "become one of them". Part of the experiment, participantsdon’t usually know. ○ Rosenhan and 7 sane people admitted to mental institutionsto see if the medical staff was accurate  Qualitative data- other patients noticed that they were not crazy. Staff responded generally to specific question  Quantitative data- days in the hospital • Contrived/ structured- construct situation so that you can measure relevant behaviors. ○ Bandura's Bobo doll experiment • Problems with observation: ○ Demand characteristics- people might do what the feel is expected of them based on clues from the researcher or design Reactivity- modify natural behavior when they know they are being watched ○ ○ Subjective- you may miss something • Experimenter expectancy effect- ○ Rosenhan found that some assistants that were told the rats were bred to learn mazes quickly found that the "smart" rats learned quicker than the people who were told the rats were bred to have difficulty. ○ In reality, all the rats were the same. ○ Avoiding this problem-  Single blind study- experimenter does not know the hypothesis or the condition the participant is in Exam 1 study guide Page 1  Single blind study- experimenter does not know the hypothesis or the condition the participant is in  Double blind study- neither experimenter nor participants knows the condition • Scientific writing: ○ Very plain, fact based ○ Anything you state as true must be supported by a reference ○ Should provide sufficient detail that a stranger could replicate the study • Title page(title, author, affi→iabstract(brief summary of entire p→peintroduction(construct, theory, literature review, hypothesis)→ methods (participants,materials, design and proc→duresult→ discussio→ reference→ figures and tables • Literature searches: ○ Acquire background knowledge on the topic ○ Basis for the investigation • Survey research: ○ General questions before specific ones ○ General demographics at the end of the survey • Open end questions:ex- are you an emotional person? • Restricted choice questions: ○ Ex- Give options ranging from "not emotional at all" to "I am an extremely emotional person" ○ Quick and easy to analyze ○ Provides quantitative data ○ Answer is biased by set of provided answers ○ Person may give an answer even though they do not understandthe question  Likert- strongly agree through strongly disagree  Semantic differential-ex- president obama is weak------strong. Intelligent-----unintelligent. Categories of meaning differentiating between two things. Give people a statement to complete or categorize. Give a category and its opposite  Quantitative- how many times do you do something? Give numbers/ ranges  Categorical- ex- my favorite color is: (give options of colors) • Potential problems with surveys: ○ Using appropriate vocab- people need to understandwhat you are asking. Consider your audience ○ Avoid words with unwanted emotional baggage. Do not want to offend people taking the survey ○ Avoid leading questions. May push a person's answer in a certain way. Ex: do you agree that…? ○ Avoid tactless questions. ○ Be clear in how you are asking things. ○ Avoid ambiguous answers. Give more specific options for answers. ○ People may just pick the same answer for every question. To avoid this, you use positive and negative statements • Population of interest (college students) -----> narrows into sample (people who took the survey) • Sample- how we select people from the population • Assignment- how you take the sample and put them into conditionsof the experiment • Bias- sample differs from population on important dimensions. We have inaccurately sampled the data ○ Populationand sample means systematically mismatch. They will never be identical due to random error. • Stability- how much noise is in the data? Unstable = not reliable. Spread/variance of the sample. ○ Improve stability with large sample size. Variance is relatively low. • Probability sampling- each member has known and nonzero change of being selected • Known- must be able to identifyand access each member of the population ○ Nonzero- everyone has a chance of being sampled ○ Simple random- everyone in the populationhas an equal chance of being selected. Ex- drawing names from a hat  Without replacement- each person can only be sampled once. Common in psych  With replacement-people can be selected multiple times Stratified- break populationinto sub-samples and choose randomly from the subsample. Makes sure you have people from each subset. Exam 1 study guide Page 2 ○ Stratified- break populationinto sub-samples and choose randomly from the subsample. Makes sure you have people from each subset. Usually relevant for your research question  Stratified random- equal number from each subset  Proportionate- sample each strata in each proportion to its size in the population • Non- probabilitysampling- not drawing from the entire population  Convenience- taking whatever you can get  Quota- selectively taking what is available according to a plan. Ex- 10 males and 10 females • Descriptive statistics- techniques that help to describe a set of data ○ Organize, summarize, and simplify the data • Mean: average. 1st: sum of the observations. 2nd: divide the sum by the total number of observations. ○ Σx / N ○ Best in most situations • Median- middle value ○ Best for extreme values that will skew the data. Ex- housing prices • Mode- shows up most often. Most common observation ○ More useful when decimals don’t make sense (number of children in a family) and categorical response scales • Normal distribution: mean= median. • Positively skewed- tail points towards the positive end. Median < mean • Negatively skewed- tail points towards the negative end. Mean < median • Standard deviation: 1. Compute the mean 2. Subtract the mean from each value 3. Square each of those 4. Add them all together 5. Divide by the number of observations -1. 6. Take the square root • Standardized score/ Z-score ○ Can convert any score (X) ○ Score= (X-M) / S ○ (Score- mean) / standard deviation ○ Ex- standard score = 0 means your score is 0 standard deviations from the mean, so your score= the mean. Standard score of +1 means your score is 1 SD above the mean • Scales of measurement: ○ Categorical/nominal- differentoptions, not ordered. Ex- gender, favorite color, etc ○ Ordinal- different and ordered. Semantic differential, likert, quantitative.Ex- rank, birth order ○ Interval/ratio- different,ordered, distance between the responses is the same. Ex- temperatures • Evaluating if a relationship exists: ○ Pearson's r- calculates a correlation statistic ○ Scatterplot- graphs the relation between the variables. Each point is 1 observation • Form- the pattern of the data. ○ Usually linear. ○ Either positive or negative • Direction- positive or negative ○ Positive- pearson's r is greater than 0. both go up or both go down ○ Negative correlation- vary in opposite directions. As x increases, y decreases. • Strength- numerical value close to +1 or -1 ○ If there is no relationship, X and Y are not related. Correlation coefficient is close to 0. ○ How "cloudy" is the scatterplot? ○ The farther from 0, the stronger the relationship ○ No relationship or correlation: ± to .09 ○ Small/weak correlation:±.10 t± .29 ○ Medium/moderate correlation: ±30 to ±49 ○ Large/strong correlatio±: .50 ±1 *****REVIEW PRACTICE QUESTIONS ON BLACKBOARD***** Exam 1 study guide Page 3 Exam 1 study guide Page 4


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