Fichas
335 Final
Fichas del conjunto (60)
- 1GISGeographical Information Systems
- 25 dimensions to model real world1. Land Use 2. elevation data 3. parcels( land division) 4. streets 5. customers
- 3How to solve problems _____Spatially
- 4GIS Datadigital data that represents real-world features, statistics & phenomena
- 5GIS data knows ___ in Geographical Space; not just a ____WHERE; PICTURE
- 6GIS =Attribute data + Spatial Data
- 75 needs for GISpeople, computer, software, data, problem or questions
- 8who uses GISEVERYONE
- 9GeocodingFinding address/location on googlemaps
- 10RoutingFinding directions on googlemaps
- 113 levels of GIS use in marketing1. where customers are
2. understand customers
3. how to target new customers - 123 levels of understanding customer using GIS(can use census) 1. how far from store 2. socio-economics of the area 3. area stats
- 13how to use GIS data to target new customersfind new areas with similar customers
- 14LIfestyles & Tapestry Datadifferent 'life-modes' to better understand cusomer
- 15GIS Skill (5)understand database, table relations, SQL queries, summary statistics, classifying data
- 16Proximity Analysiswhats around you, vicinity
- 17when analyzing a map, need to knowHOW IT WAS MADE
- 18Where GIS data comes from1. Make it 2. Remotely Gather 3. Obtain from other sources (Census)
- 194 Virtual Reality examplesKorean Grocery store in subway, Toronto convenience store in subway, 3D visualization french grocery store, Addidas Virtual Wall
- 20When was 3D first invented1950s
- 21How to use in MarketingVirtual shopping, understand customers: in store and interacting with product
- 22virtual Advertisingoverlay with reality, needs to add to the experience
- 23Download data from Qualtrics in the ____ format.csv comma separated values
- 24questions/variables are located in thecolumns
- 25participants are located in therows
- 26Process for Paper SurveysID each survey after completed, hand enter data into Excel, make note of which ones in case of instrumental error
- 27Why is simplicity in your database importantto not confuse the statistical analysis programs
- 28Flipped scale questionsre-code before analysis
- 29multi-item measureadd extra row for a sum of scores, also before the analysis
- 30column headings must have< 8 letters and start with a letter
- 31recognize the coding fromQualtrics, don't change and make new
- 32two main views in SPSSData View and Variable View
- 33Data ViewJust like the spreadsheet
- 34Variable Viewlists all variables, some are measured on different dimensions
- 35levels of measurements in Variable Viewordinal, nominal, scale (interval, ratio)
- 36Clean Data: missed responsesCheck with frequency tables
- 37Clean Data: Collapse Datanot enough of one demographic/ category, create a new variable
- 38Clean Data: Sum Variablecombine into single measure
- 39Assessing Reliabilityuse Cronbachs Alpha (0-1), closer to 1 = highly correlated and reliable measure
- 40in Chi Square: Null Hypothesis =no difference in Chi Square
- 41P-Value =probability null hypothesis is true
- 42reject null hypothesis (there is evidence support) IfP-value < .05
- 43Use T-test whenComparing 2 means
- 44Use an ANOVAwhen comparing 3+ means
- 453 kinds of T-tests1- sample, independent Samples, Paired Samples
- 46one-Sample T-testcompare responses to fixed values
- 47Independent Samples T-testCompare 2 pple for same questions
- 48Paired Samples T-TestCompare responses from same people for different questions
- 49Repeated Measures ANOVAPost-hoc analysis, determines where the differences lie
- 50What makes good eye-tracking data? (5)color, single page, multi AOIs, Headline. copy. logo., not too complex
- 51What do we measure with eye-tracking (5)1. time to first fixation 2. first fixation duration 3. Fixation count 4. visit duration 5. percentage fixed
- 52time to first fixationtime from start of stimulus until participant fixates on AOI for first time
- 53First Fixation Durationhow long the first fixation lasts
- 54Fixation Countsnumber of times participant fixated on an AOI
- 55Visit Durationduration of each individual visit within AOI
- 56Percentage FixatedPercentage of participants who fixated at least once on AOI
- 57Heat Mapbrighter colors if they spent more time there
- 58opacity maponly shows the areas highly looked at (blacks out other areas)
- 59Gaze PlotShows the sequence their gaze followed
- 60Descriptive Statisticsquantitatively describing data
Información
- Descripción
- Fichas sobre 335 Final, creado por gerlacca el 09/12/2013.
- Creado por
- gerlacca
- Visitas
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- Valoración