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Variable
Median
Mode
Range
Data
Label
Sample
Cluster
Graph
Trend
Outlier
Certain
Unlikely
likely
Impossible
Probability
Investigation
Classify
Discrete

# data[].attributes.body
data
graph
mean
median
range
probability
even
certain
likely
unlikely
impossible
title
axes
label
theoretical
example
percentage
cluster
trend
calculate
fraction
statistical
evaluate
number
decimal
data
rules
relationship
possibility
sample
display
results
pie chart
population
pictograph
bar chart
time series graph
column graph
stem and leaf graph
dot plot
range
identify
compare
distance
continuous
discrete
total
alpha
bias
box plot
categorical
exhaustive

# data[].attributes.body
data
trend
theoretical
variable
subject
median
mode
range
axes
certain
cluster
even
probability
graph
calculate
investigation
tally chart
certain
impossible
likely
unlikely
fraction
percent
conclusion
biased
evaluate
title
Oneal
evaluate
compare
parameter
outlier
table
sample
experimental
list
calculate
analyse
colum graph
dot plot graph
time series graph
census
combination
discrete data
continous data
relationship
grouped data
total
double bar chart
raw data
box plot
skew
combination
alpha
Hypothesis.

# data[].attributes.body
data
graph
variable
tittle
label
certain
range
sample
skew
example
compare
axes
certain
impossible
solution
investigation
mearsure
cluster
out-liner
discrete
group
left
classify

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title
graph
cluster
trend
outlier
even
likely hood
mean
meadian
data
variable
range
probability
unlikely
likly
sample
conclusion
analise
certain
inpossible
pie chart
dot plot graph
tally chart
bar graph
experimental
biased
pictogram
scatterplot graph
analyze
variable
sample
box and wisker graph
sensus
average
coloum graph
discreat
scale
double bar chart
measured
compare
grouped
investigate
grouped data
results
evidence
prediction
problem
plan
raw

# data[].attributes.body
Data
mean
median
range
graph
probability
investigation
chart
title
label
variable
cluster
trend
even
likely
unlikely
possible
impossible
certain
tally
experimental
conclusion
relation
solotion
analyse
sample
axis
scale
chance
calculate
diagram
table
list
outlier
skew
combination
discrete
categorized
column graph
dot plot
bar chart
pie chart

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DATA
MEDIAN
AVERAGE
Range
Axis
Parameter
Trend
Cluster
Tally
Scale
Solution
Certain
Even
Sample
Chance
Outlier
Diagram
Table
List
Theoretical
Combination
skew
Rules
Discrete
Mean
Catagorize
Measure
Graphs
Analyse
Bundle

# data[].attributes.body
Title
X axis
Y axis
Mean
Median
Range
Dot plot graph
pie Chart
certain
trend
analyze
variable
Outlier
approximately
fluctuated
Sample
likely
unlikely
discrete data
tally  chart
Pictogram
Time series graph
Theoritical probability
Statistical Literacy
Frequency
Decline
cannot use all but can use most
grouped data
experimental
Labels
continuous data
relationship
probabilit

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probability= the likely hood of something happening

Data= the results of a test

range= the amount of space between to numbers

Continuous data= data that is measured on a continuum of scale

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Variable
Mean
Median
Mode
Range
Theoretical
Title
Label
Conclusion
Investigation
Graph
Sample
Population
Certain
Analyse
Skew
Data
Experiment
Outlier
Discrete
Trend
Axis
Relation
Charts
Probability

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Analyse
Discrete
Hypothesis
Grouped
Average
Repesent
Grouped Data
Results
Chart
Most
Peak
Compares
Trend
Fairly
Fluctuated
Approximateley
Evidence
Rare
Pie Chart
Pictogram
Bar chart
Stem and leaf chart
Data
Range
Theoretical
Experimental
Frequency
Mean
Median
Mode
Conclusion
Title
Labels
Axis
Graph
Cluster
Outlier
Rare
Relation
Probability
Sample
Calculate
Evaluate
Outcome

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Theoretical
Experimental
Title
Compare
Label
Conclusion
Probability
Median
Mean
Mode
Range
Relations
Trend
Sample
Graph
Axis
Analyze
Information
Cluster
Example
Biased
Data
Discrete data
Continuous Data

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Oneal
conclusion
graph
theoretical variablerange

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title
information
variable
chart
data
investigation
mean
mode
median
range
conclusion
sample
even
fair
discrete
skewed
theory
outlier

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conclusion
analyse
title
trend
x axis
y axis

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Median
Analyse
Mean
Medium
Range
Value
Graph
Theory
Data
Probability
Mode
Investigation
Sample
Y Axis X Axis
Trend
Outlier
Frequency
Conclusion
Title
Label
Info
Proof
Line Graph
Dot Plot Graph

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Data
Variable
Probability
Even
Certain
Title
Median
Mean
Mode
Time Series Graph
Pie Graph
Dot Plot
Pictograph
Range
Sample
Bar Graph
Outlier
skew
Tally
Estimate
Discrete

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Statistics
Data
Variable
Graph
Median
Mean
Range
Mode
Title
Probability
Likely
Analyse
Relationship
Theory
Frequency
Certain
Likelihood
Impossible
Discrete
Outlier
Pattern
Estimate
Axis
Example
Trend
Sample
Continuous
Cluster
Investigation

# data[].attributes.body
Variable
Median
Graph
Theoretical
Analyse
Probability
Data
Certain
Range
Mean
Mode
Y axis X axis
proof
evidence
trend
cluster
title
label
sample
outlier

# data[].attributes.body
label
data
graphs
information
proof
evidence
median
analyse
trend
cluster
tittle
variable
range
mode
mean
peak
probability
rang
relationship
rules
stats
sample
even
petition
population
leaf
stem and leaf
dot graph
pie
bar
picture gram
out-liner
skew
scenes
lists
equal
describe
Deseret

# data[].attributes.body
Label
Title
Variable
Value
Graph
Data
Sample
Median
Mean
Range
Theoretical Probability
Analyse
Tree Diagram
Outlier
Trend
Stats
Questionare
Discrete
Continuous
Investigation
Evidence
Likely
Chance
Tally
Frequency

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Probability
Title
Theoretical
Median
Graph
Analyzing
Cluster
Variable
Certain
Equal
Data
Range
Relationship
Rules
Sample
Population
Census
Experimental
Statistical
Bi est
Evaluate
Evidence
Appropriateness
Likelihood
Event
Describe
Diagrams
Outcomes
Tables
Lists
Scale
Calculate
Skewed
Decimal
Display
Results
Likely
Important
Impossible
Possible
Certain
Info
Proof
Value
Conclusion
Square Root law
Standard
Scampling
Continuous
Mean
Bar graph
Pie chart
Pictogram
Y axis X axis
Discrete
Solution
Tally
Trend
Cluster
Grouped Data
Label
Histograms
Height
Categories
Bundled
Fraction
Number
Total
Alpha
Even
Mode
Percentage
Oneal
Unlikely
Classify
Outlier
Investigations

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WHAT IS A VARIABLE

# data[].attributes.attachment_link.description
A three minute video on what a variable is in statistics classes. Often students use variables, take tests on variables, but don't really know what the essential concept means. This short video can help students get a fundamental understanding that I hope will enhance their understanding of statistics, and hopefully will foster interested, rather than "getting that course out of the way."

# data[].attributes.attachment_link.readable_text
Data can be Descriptive (like "high" or "fast") or Numerical (numbers).

And Numerical Data can be Discrete or Continuous:

Discrete data is counted,
Continuous data is measured

Discrete Data

Discrete Data can only take certain values.

Example: the number of students in a class

We can't have half a student!

Example: the results of rolling 2 dice

Only has the values 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12

Continuous Data

Continuous Data can take any value (within a range)

Examples:

A person's height: could be any value (within the range of human heights), not just certain fixed heights,

Time in a race: you could even measure it to fractions of a second,

A dog's weight,

The length of a leaf,

Lots more!

# data[].attributes.attachment_link.description
Data can be Descriptive (like "high" or "fast") or Numerical (numbers). And Numerical Data can be Discrete or Continuous: Discrete data is counted, Continuous data is measured Discrete Data can only take certain values. We can't have half a student!