Topic 8

Question 1

what is a histogram

Answer 1

graph showing the frequency of measurements/obeservations plotted against the range of observations

an important data exploration and summary tool

Question 2

explain modality and symmetry

Answer 2

median - 50% higher and 50% lower
skew… what way is the tail facing

Question 3

symmetrical distribution

Answer 3

mode, median, mode are coincident

Question 4

modality

Answer 4

when there are more than one value with a high frequency

greatly impacts the use of median and mean measures

Question 5

sample mean vs population mean

Answer 5

divided by the sample number or entire population

Question 6

we use deviation from mean ro deviation from the median

Answer 6

median is more popular because it doesnt get so easily affected by outliers

Question 7

standard deviation is important with data transformations T/F?

Answer 7

true

Question 8

what is data normalization

Answer 8

raw totals (Numerator) are standardized against a denominator
min-max scaling
comparing something to make it comprehensible

Question 9

standardization (z-score normalization)

Answer 9

types of normalization
denominator is standard deviation
max is 1
min is 0
goes to 0

Question 10

min-max scaling

Answer 10

important for rasters
range of data
min and max values
does not go to 0 only to the min value

Question 11

how do you know when you need to standardize your data?

Answer 11

know your data before normalizing it. Normalizing unrelated data is like mixing apples and oragnes. It makes fruit salad, not a good analysis

not all variables need to be normalized

results can be proportions or percentages

Question 12

data classification considerations

Answer 12

grouping of numerical data into classes for mapping, with each class represented by an individual symbol

class interval: where to put breaks in the data
number of intervals : 4-7

Question 13

describe equal intervals

Answer 13

equal intervals or steps along the number line
determine data range
not very good
susceptible to outliers

Question 14

describe quantiles

Answer 14

each class contains the same number of observations/values
easy tp understand

Question 15

describe mean standard deviation

Answer 15

derive classes from the descriptive statistics of overall data distribution
worst method

Question 16

maximum breakes (defined interval)

Answer 16

derive classes from groups of similar data values according to local citerion
calculation of classes order data from low to high
use largest differences as class breaks
can be good
susceptible to outliers
you dont see contrast

Question 17

natural breaks

Answer 17

subjective, visual/manual determination of logical breaks in data distribution in dispersion graph or histogram
depends on what you want to highlight

Question 18

geoeetrical intervals

Answer 18

class breaks are based on a geoetric series
good for highly skewed data
good for computers

Question 19

optimal (fisher-jenks)

Answer 19

computational approaches to mimimizing classification error
most common method
indentifies low points in data

Question 20

rating of classification methods major points

Answer 20

quantiles is only good for ordinal data
optimal is only good one for helping assist with selecting number of classes

Question 21

enumeration and spatial fallacies

Answer 21

areal aggregation
census tracts
best when units are similar sizes

MAUP
depending on the geometry of spatial organization impacts your outcome and how it will look on the map
change the area = change results

Question 22

jenks (optimal) tends to stay away from using mean as a central measure T/F?

Answer 22

True

Question 23

what is multivariate mapping

Answer 23

encoding two or more variables into the symbolization

trade off between the information content and the complexitiy of the map

two main groups
inter-symbol encoding
intra-symbol encoding

bivariate choropleth maps
bivariate normalization (value by alpha)

Question 24

what is inter-symbol encoding

Answer 24

symbolize 2 symbols concurrently (complimentary symbols)

Question 25

what is intra-symbol coding

Answer 25

multiple visual variables in one symbol
combination of size and hue could be applied

Question 26

selection of colour for classed maps

Answer 26

kind of data
colour vision impairment
simultaneous contrast
colour associations - cognitive
aesthetics
purpose - exploration vs presentation
cost of production

Question 27

uni polar vs bipolar data characteristics

Answer 27

unipolar - sequential
lightness usually preferred - varying saturation cna enhance visual contrast

bipolar - diverging
two hues diverge from a common light hue or grey

Question 28

representing uncertainty

Answer 28

accuracy and precision
uncertainty - difference between the real geographic phenomena and the users understanding of the phenomena

ex. inaccuracy of inerpolated maps
completeness of census data
nature of data collection - standardized methods or not

Question 29

grouping techniques

intrinsic-extrinsic

coincident-adjacent

Answer 29

intrinsic - extrinsic
intrinsic = vary existing object
extrinsic = use new object
coincident-adjacent
coincident = shown in same frame
adjacent = small multiple
static-dynmic
dynamic = animations or interactivity

Question 30

colour schemes and classified maps

Answer 30

map readers process colour by seeing differences in hue, stauration, and value

mapping different “things”
saturation (changing lightness)
hues ( best used to identify map featueres and differentiate)
value (lightness )

Question 31

Look up tables

Answer 31

LUTs are used in lots of ways
data structures that map values of attributes to something else
colour scale can be lenghtened by adding saturation
keep hue constant but vary saturation and lightness

look up tables = enhancement

Question 32

what type of data is pseudo colour table used on

Answer 32

unclassed data

Question 33

what is an anthrom?

Answer 33

human controlled ecosystem

Question 34

3 type of histogram graphs with LUTs

Answer 34

linear stretch (min-max enhancements)
exponential stretch
logarithmic stretch

Question 35

are stretch and enhancement synonymous terms?

Answer 35

yes

Question 36

what method is best used with contrast stretch

Answer 36

standard deviation