# data[].attributes.body
there is no correlation between height and temperature outside

# data[].attributes.body
as the salt added increases, the thickness of ice also increases

# data[].attributes.body
salt increase=ice decrease

# data[].attributes.body
as the temperature increases, the sales of drinks also increases

# data[].attributes.body
as they get taller, the height of the student also increases

# data[].attributes.body
as temperature increases drink sold will increase

# data[].attributes.body
as amount of people increases, restaurant sales also increases

# data[].attributes.body
as time shopping increases, money spent decreases

# data[].attributes.body
1.39 is a invalid score

# data[].attributes.body
0.99 is a strong positive

# data[].attributes.body
height increase Iq decrease

# data[].attributes.body
time studied (x) vs test score (y)

# data[].attributes.body
Boxes

# data[].attributes.body
time running vs heart rate

# data[].attributes.body
As you typing increases, your search history in this world increases.

# data[].attributes.body
As more people change their power sources increases, pollution decreases (but only by a little bit).

# data[].attributes.body
As the number of food supplies increases, the number of people fed increases.

# data[].attributes.body
As the number of pizza increases, the number of bowling alleys increases.

# data[].attributes.body
0.00

# data[].attributes.body
As the amount of salt increases, the thickness of the ice will decrease.

# data[].attributes.body
as outdoor temp increases, height increases

# data[].attributes.body
as time increases, phone sales decreases

# data[].attributes.body
as YouTube views increases, subscribers increases

# data[].attributes.body
as student height increases, test score increases

# data[].attributes.body
As temperatures increase, ice cream sales increase

# data[].attributes.body
time building vs supplies left

# data[].attributes.body
1.43 = invalid

# data[].attributes.body
As height increases, weight decreases.

# data[].attributes.headline
As memes increase, legend status increases

# data[].attributes.subject
As memes increase, legend status increases

# data[].attributes.body
As the the time in school increases, the time to work decreases.

# data[].attributes.body
1.11

# data[].attributes.body
as time increases, money value decreases

# data[].attributes.body
an invalid r score would be 1.32

# data[].attributes.body
1.36

# data[].attributes.body
1.85

# data[].attributes.body
0.99 = strong

# data[].attributes.body
0.57 moderate positive

# data[].attributes.body
0.93 = strong positive

# data[].attributes.body
0.85 = Strong positive

# data[].attributes.body
0.00 = No Correlation

-32.10 = INVALID r-score

As more memes are being posted on this Padlet increases, the space left for post decreases.

6'3.5"

As temperature increases outside, lemonade sales increase.

As the amount of salt increases the thickness of the ice decreases.

As tempature outside increases, your height neither increases or decreases.

# data[].attributes.body
0.90 strong positive R score

# data[].attributes.body
Invalid r-score 1.21

# data[].attributes.body
0.96 = Strong Positive

-1.44 = Invalid R-score

Bivariate data
Time shopping increases, Money spent decreases.

Univariate data
As height increases, game time increases.

Correlation
As my social media likes increasing, my social media followers increases.

Correlation
Salt increases, thickness decreases.

0 Correlation
As outdoor temp increases, height increases.

# data[].attributes.body
0.94 is a strong positive.
The R score is positive.
The R score is invalid.

As time increases, money value decreases.

As a student's height increases, their speed decreases.

As the temperature increases, the ice decreases.

As groceries increases, prices decreases

0.00

# data[].attributes.body
Bivariate data w/example
time shopping vs money spent

# data[].attributes.body
Univariate data w/example
Student height

# data[].attributes.body
- correlation example
salt added vs ice thickness

# data[].attributes.body
+ correaltion example
outdoor temp(x) drinks sold(y)

# data[].attributes.body
0 correlation example - Outdoor temp vs height

# data[].attributes.body
r - score w/meaning
0.85 strong positive