Data Visualization Data Science

Data Visualization is used to communicate information clearly and efficiently to users by the usage of information graphics such as tables and charts.

Data Visualization helps users in analyzing a large amount of data in a simpler way.

Data Visualization makes complex data more accessible, understandable, and usable.

All of the above

graphs

charts

maps

All of the above

deliver presentation architecture

data presentation architecture

dataset presentation architecture

data process architecture

Treemaps

Scatter plots

Population pyramids

Area charts

fisher.test()

chisq.test()

Lm.test()

prop.test()

factor.mosaicplot

factor.xyplot

factor.congruence

factor.cumsum

qqline()

qline()

anova()

lm()

data visualization include the ability to absorb information quickly

Data visualization is another form of visual art

Data visualization decrease the insights and take solwer decisions

None Of the above

Politics

Sales and marketing

Healthcare

All of the above

Autocausation

Autorank

Autocorrelation

None of the above

It can be accessed quickly by a wider audience.

It can misrepresent information

It can be distracting

None Of the above

It conveys a lot of information in a small space.

It makes your report more visually appealing.

visual data is distorted or excessively used.

None Of the above

Bullet Graphs

Bubble Clouds

Fever Maps

Heat Maps

Line charts

Scatter plots

Population pyramids

Area charts

anova()

par()

plot()

cum()

rep()

data()

view()

read()

lm()

col.max

par

histo

par()

names()

barchart()

quantile()

Scientific visualization, sometimes referred to in shorthand as SciVis

Healthcare professionals frequently use choropleth maps to visualize important health data.

Candlestick charts are used as trading tools and help finance professionals analyze price movements over time

All of the above

par

lm

kde

C