Comm 150 Week Four Notes
Comm 150 Week Four Notes Communication Studies 150
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Communication Studies 150
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This 8 page Class Notes was uploaded by Alyssa Notetaker on Wednesday October 21, 2015. The Class Notes belongs to Communication Studies 150 at University of California - Los Angeles taught by PJ Lamberson in Fall 2015. Since its upload, it has received 57 views. For similar materials see Methodologies in Communication Research in Communication Studies at University of California - Los Angeles.
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Date Created: 10/21/15
Week Four Lecture Seven Discussion big data example cont d Operationalizing 0 Define I Sickness at least 2 of the following temperature over 100 degrees sore throat stuffy nose coughing more than 5 times every hour Indicators of sickness buying at least one of the following within two weeks of buying 0 and potato chips a thermometer emergenC Dayquil and or Nyquil generic cough and cold medication cough drops 0 Binary nominal ordinal interval ratio I Binary did they buy it or did they not How to collect the data narrow in on what big data to use 0 Narrow in on O potato chips and subsequent cold medication purposes Target population all Walmart customers 0 Sample frame stratified sample with all the Walmarts in each state as a different stratum for the sample choose a statistically sufficient number of stores to look at from each stratum find every person to meet the criteria in each of those stores 0 Does the sample frame differ systematically from the target population I No it is the same Observed value true value error 0 Potential for error no systematic error because we are not interacting directly with the customers 0 There is always a chance of random error Experimentation Sample question what is the effect of television viewing on political behavior More specifically does television cause people to place more emphasis on image than candidates stances on issues What is the impact of television rather than radio on how much emphasis citizens place on image On how television affects political behavior 0 Experiment randomly select a sample of people to survey randomly choose half to listen to a radio broadcast and answer questions the other half watched a TV broadcast with the same words but with an image too of landscape rather than people to eliminate racial gender biases and have them answer the same questions multiple choice See if differences are statistically significant 0 Another see how long people focus with radio vs with TV how long they ll watch or listen before leaving 0 Play debate on radio vs on TV quiz them on information about the debate see who retained more information I To eliminate previous knowledge have a pretest I But this could threaten internal validity with testing bias giving someone a pretest could give away what the researcher is looking for and they ll be looking for the answers to the questions they were just asked This can impact how they watchlisten and so impact the results Would need to have a second experiment test half the people with a pretest half without so a quarter with pretest and radio quarter with no pretest and radio quarter with pretest and TV and a quarter with no pretest and TV see if pretest affects results too But if it s randomized don t need to worry about previous knowledge 0 It ll tend to cancel out be distributed between the two groups test and control group Threats to internal validity Testing bias 0 The way in which the measurement is taken changes the response 0 When the test experiment itself in uences the subjects responses 0 Ex a pretest primes subjects as to what the researcher is looking for in uences how they act in the experiment 0 Similar to experimental bias demand characteristics reactive measurement effects Instrumentation o The way in which the measurement is taken changes over time I Unwanted changes in characteristics of the measuring instrument or in the measurement process 0 Can get more accurate less accurate change qualitative standard standard of good vs bad changes as you see better or worse examples I Ex A person hired to count events gets bored and less accurate as time passes I Ex someone gets better at measuring as time goes on I Ex a professor grading exams Selection bias when there are systematic differences between the composition of the control and treatment groups 0 Ex selfselection selfreporting people report if they listen to radio or watch TV then are asked to answer some questions the results could be because more politically inclined people choose to listen to radio or something and not because listening to the radio causes them to be more politically inclined endogeneity o Confounders lack of causation I Ex more accidents where there are crosswalks confounder more people use crosswalks than not and more dangerous O O streets have crosswalks so should not conclude that crosswalks cause accidents Ex people who sign up for the treatment it s not random Avoid with random assignment History if something is widely known people will be affected by it 0 O 0 When other events in the environment might affect the outcome Ex showing debate between Hillary and Bernie the experiment would be affected by everyone being biased by the pundits opinions the official result etc But if use fake politicians could affect it because actors could be really good looking or better at moving on stage than politicians so the TV group would be really affected by that Ex if you do an experiment over 2 days and the people who do it the first day talk to the people who will do it the second day Ex doing an experiment over two days and in the time between the two experiments something could happen that in uences the results Maturation 0 When changes take place within subjects over time during the course of the experiment I Ex if the experiment goes on for a long time the subject can get tired bored hungry etc I Ex doing an experiment on two different days and it takes longer to set up on the first day and people were waiting on the experiment to start I Ex testing on Monday and Tuesday people on Monday might be more tired or more rested Statistical Regression 0 Extreme measurements tend to move closer to the mean on second observation Ex people who score low on a pretest are likely to score closer to the average on a posttest I Taking a test primes the subject for taking tests so they do better I Higher scores are likely to decrease on the second test Ex using a pretest of racial bias to assign people to a treatment a video to reduce their bias I If a person scores high on the pretest seems racist they are more likely to score more average on the second test just because and so it would seem like they re less racist after watching the video Looks like there was an affect when there was none I So never use a test to assign people to treatments I Keep assignment random Attrition the loss of subjects in an experiment 0 Greatest threat when there is differential attrition when the conditions of the experiment the test group 1 2 control etc have different dropout rates Can confound the experiment Preexperimental Designs Use debaters from one party to reduce variation Use matching to randomly assign the same number of each democrats and republicans to each TV and radio 1 Oneshot case study some treatment is administered to one group after which the group is observed or tested for treatment effects 0 No control or second test group possibility for attrition maturation history and other confounders 2 Onegroup pretestposttest design O 0 Observe a group of subjects pretest introduce the treatment experiment with independent variable observe posttest Allows comparison controls for attrition checks who was there before and after No control possibility for testing bias as the pretest could affect the subjects views of what s happening also maturation history instrumentation statistical regression 3 The static group comparison 0 O 0 Two groups one receives treatment and the other doesn t both are observed afterward posttest Has a control Also controls for history because both groups should have pretty much the same history and for testing and statistical regression since it doesn t have a pretest Still threats to internal validity selection not necessarily randomized attrition maturation if not done simultaneously True Experimental Designs 4 The pretestposttest control group design 0 O Randomly assign subjects to 2 groups observe both pretest apply treatment to one observe both posttest External validity threat testing interacting with the independent variable aka testingtreatment interaction in other words the results of the treatment could be different than they would be without a pretest 5 The posttestonly control group design O O Randomly assign the subjects to 2 groups treat one observe results of both This is more economical and eliminates the possibility of testing treatment interaction But chance of attrition if it s a long term experiment 6 The Solomon fourgroup design O Randomly assign subjects to 4 groups I Observe pretest only two of them I Test apply the treatment to one of the pretested groups and one of the nonpretested groups I Observe all groups posttest compare to see the effect of the treatment and the effect if any the pretest had Withinsubjects design have both treatments apply to the same subject 0 Don t have to use so many people reduce issues of individual differences some are more informed from different parties etc o Comparing someone to themself I each person acts as their own control 0 Issues I Subject can be affected by which goes first Solution test if there is an order effect by randomly assigning half to see TV first half to hear radio first Counterbalancing I The subject can figure out what the researcher is studying Hiding the real experiment to simulate reality avoid experiment effects experimental bias where people change their behavior because they know they re being tested 0 Ex Testing endowment effect once someone has something they are less likely to give it up 0 In waiting room waiting to take a survey as part of an experiment given a chocolate bar then later offered a mug Other test group vice versa Control offer both at the same time o The real test is hidden from the subjects Factorial Experimental Designs Social phenomena are often caused or in uenced by multiple variables So factorial designs allow researchers to study several independent variables at once Some types of factorial designs 0 2x2 factorial design is when there are 2 factors independent variables each with 2 levels I Ex the Solomon fourgroup design 2 independent variables pretest and treatment 2 levels each whether or not the group is pretested whether or not the group is treated 4 total conditions pretest treated pretest not treated no pretest treated no pretest not treated I Has 4 total conditions 0 3x4 factorial design 3 independent variables each with 4 levels I 12 conditions Factorial designs provide information about the main effect of each factor 0 Aka the overall effect of the factor by itself 0 Found by comparing the overall means of each condition I Ex compare the overall means of the treated groups and the nontreated groups to see the effect of the treatment I Compare the overall means of the pretested group and the nonpretested group to see the effect of the pretest Interaction Effects Gives us information about the joint effects of the factors together for example the treated and pretested vs the nontreated and nonpretested To see visually graph the means of each condition by factor 14 12 H D Task 1 Task 2 Control Treatment 0 Condition 0 Each line represents a condition for example blue shows pretested and red shows nonpretested and the nontreated and treated points are on the Xaxis I How it is shown the treatment affects the subjects in all cases but more so when the subjects were pretested I If the red line were at it would show the treatment had no effect and all the seen effects were due to the pretest I If the blue line were at it would show the pretest had no effect I If they re parallel it shows they had no effect on each other no interaction Quasiexperimental designs Separatesample pretestposttest design 0 Randomly assign subjects to two groups observe one pretest test both observe the other one posttest 0 Most serious threat to validity history Nonequivalent control group designs 0 Where the researcher uses already intact groups like school classes 0 So random assignment is impossible Interrupted timeseries design 0 Multiple observations before and after the treatment 0 Threat from history instrumentation if you re looking at records and there has been a change in recordkeeping procedures 0 This with 2 groups one with and one without treatment multiple timeseries design Performance O N A O 03 Lecture Eight Surveys 3 Stages to surveys after hypothesis operationalization etc Sample Survey Analyze Conversational norms Our norms can affect how someone takes or understands a survey 0 Be truthful 0 Be relevant on topic 0 Don t repeat 0 Be clear So if we ask two synonymous questions that are worded differently Considerations Open v closed questions 0 Open more information more open for interpretation allows the person to submit whatever answer is most relevant to them I Can allow for more information doesn t enforce your own biases on what s important You can find out if you re looking in the right direction I To get a quantifiable answer coding Have predetermined categories of answers and after the survey categorize each person s answer into one of the categories Possible to automate the coding process set a computer to find certain phrases and automate the counting of the types of each response 0 Closed have to answer with a menu of options can give a very precise answer guarantees a certain type of answer Easier to quantify Direct v indirect 0 Direct ask exactly what you want to know 0 Indirect ex do a hypothetical situation between people who are not the interviewee I if someone is invited over to Net ix and chill with someone else how likely do you think it is they will sleep together I Best to use when there s a chance of bias criminal activity touchy subjects etc Response format yesno categorical numeric scale etc Visual aids 0 Be careful of inadvertently introducing a picture that would in uence people to give a certain answer 0 Ex if we want to know how healthy someone is as in not sickly we wouldn t want to use a picture of someone working out which would have people associate the quiz with how athletically healthy they are 0 The visuals can also clarify what type of answer you re looking for Question order Rules of thumb for questions Keep it simple and clear Address one issue per question Don t ask loaded questions ex Don t you agree thatquot Avoid emotionally charged language Avoid double negatives
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