D772 Statistical Data Literacy Essentials: Core
Concepts, Visuals, and Probability Made Easy
Statistical Data Literacy
To help you read, question, and use statistics wisely by checking credibility, interpreting graphs, and
applying probability.
Competencies in D772
1) Determining credibility of research and data, 2) Interpreting data using statistics and graphs, 3)
Applying probability principles.
Determining Credibility of Data
Evaluating whether data is biased, reliable, and collected correctly.
Interpreting Data Using Statistics and Graphs
Reading and explaining charts, measuring center/spread, and identifying outliers.
Applying Probability
Using probability rules, expected value, and chance to make real-world decisions.
Detective-style question
"Where did this number come from, and does it really mean what they say it means?"
Population in statistics
The entire group being studied (e.g., all students at a school).
Sample in statistics
A smaller group taken from the population to represent it.
Parameter
A numerical summary of a population (e.g., true average height of all U.S. women).
, Statistic
A numerical summary of a sample, used to estimate a population parameter.
Variable
A characteristic measured from individuals in a study (e.g., age, gender, income).
Quantitative variables
Numerical values (e.g., height, weight, GPA).
Categorical variables
Labels or groups (e.g., race, favorite color, yes/no answers).
Simple random sampling
Every individual has an equal chance of being chosen. (Memory: "Names in a hat.")
Stratified sampling
Divide into groups (strata) and sample from each group. (Visual: A layered cake, slice includes every
layer.)
Cluster sampling
Divide into clusters, pick some clusters, take everyone inside. (Visual: Picking whole orange slices, not
bits of every fruit.)
Systematic sampling
Select every nth individual after a random start. (Visual: Climbing stairs, step every 5th one.)
Sampling bias
Sample doesn't represent population.
Voluntary response bias
Only loudest voices respond. (Memory: Yelp rants.)
Non-response bias
Many selected don't answer. (Visual: Empty chairs.)
Response bias
People give false/misleading answers. (Example: underage drinking survey.)
Loaded question
A question designed to push people toward an answer. (Memory: Loaded gun, already aimed.)
Self-interest study
Concepts, Visuals, and Probability Made Easy
Statistical Data Literacy
To help you read, question, and use statistics wisely by checking credibility, interpreting graphs, and
applying probability.
Competencies in D772
1) Determining credibility of research and data, 2) Interpreting data using statistics and graphs, 3)
Applying probability principles.
Determining Credibility of Data
Evaluating whether data is biased, reliable, and collected correctly.
Interpreting Data Using Statistics and Graphs
Reading and explaining charts, measuring center/spread, and identifying outliers.
Applying Probability
Using probability rules, expected value, and chance to make real-world decisions.
Detective-style question
"Where did this number come from, and does it really mean what they say it means?"
Population in statistics
The entire group being studied (e.g., all students at a school).
Sample in statistics
A smaller group taken from the population to represent it.
Parameter
A numerical summary of a population (e.g., true average height of all U.S. women).
, Statistic
A numerical summary of a sample, used to estimate a population parameter.
Variable
A characteristic measured from individuals in a study (e.g., age, gender, income).
Quantitative variables
Numerical values (e.g., height, weight, GPA).
Categorical variables
Labels or groups (e.g., race, favorite color, yes/no answers).
Simple random sampling
Every individual has an equal chance of being chosen. (Memory: "Names in a hat.")
Stratified sampling
Divide into groups (strata) and sample from each group. (Visual: A layered cake, slice includes every
layer.)
Cluster sampling
Divide into clusters, pick some clusters, take everyone inside. (Visual: Picking whole orange slices, not
bits of every fruit.)
Systematic sampling
Select every nth individual after a random start. (Visual: Climbing stairs, step every 5th one.)
Sampling bias
Sample doesn't represent population.
Voluntary response bias
Only loudest voices respond. (Memory: Yelp rants.)
Non-response bias
Many selected don't answer. (Visual: Empty chairs.)
Response bias
People give false/misleading answers. (Example: underage drinking survey.)
Loaded question
A question designed to push people toward an answer. (Memory: Loaded gun, already aimed.)
Self-interest study
