OnRamps Statistics Chapter 1 Review

Data

100

Study that involves the collection, organization, description, analysis, and interpretation of data

Statistics

200

Data in its original form

Raw Data

300

used to summarize, visualize, and describe different types of data

Descriptive Statistics

400

Name a way raw data can be transformed into a statistic

Counting, ordering, or finding the average

500

An attempt to make a prediction based on the data we collect and analyze

Inference

Data Types

100

Variables that are typically integers representing a count of objects or abstract amounts

Discrete (variables)

200

The type of variables used in a Likert scale

Ordinal (variables)

300

Type of data representing year of birth (correct for our class)

Discrete

400

Explain the difference between nominal and ordinal data

Nominal data cannot be ordered in a linear way, ordinal data can be ordered in a obvious, linear way

500

Both ordinal and discrete data can be ordered with numbers. Name the difference between these two types of data

Discrete data represents objects that have been counted, ordinal data numbers are just assigned and don't represent counts

Sample Types

100

Type of sample that involves a newspaper, online website, or standing at the exit of the lunchroom

Convenience sample

200

Type of sample that involves separating population into clusters and selecting random members from each cluster

Stratified random sample

300

The type of sample that is the ideal, where each member of the population has an equal likelihood of being selected

Simple random sample

400

You survey 50 seniors asking about what theme they'd like for prom this year. Explain the difference between parameter of interest and statistic with this example.

Parameter of interest = proportion of whole senior population that want a particular theme

Statistic = proportion of sample of 50 seniors who want a particular theme

500

The natural variation from sample to sample that happens by chance

Sampling error

Vocabulary

100

systematic discrepancy between a sample estimate and population parameter

Bias

200

Happens when sample subjects are self-selected by people volunteering to be in a study

Voluntary response bias

300

a collection of all possible subjects we are interested in

Population

400

A group from the population is called a...

Sample

500

An unmeasured variable that may mask or distort the relationship between variables of interest 

Confounding/Lurking Variables

Classifying Data Types

100

College Major 

Nominal

200

Grade Level

Ordinal

300

Temperature outside

Continuous

400

Number of absences you have in a class

Discreet

500

Jersey Number 

Nominal