Show:
Definitions
Quan vs. Qual
Population vs. Sample
Types of sampling
True/False
100
Population
What is the whole part of a group
100

weight

What is QUAN

100
Florida/ Young people in Florida
What is Florida (p)/ Young people in Florida (s)
100

This type of sampling gives every individual in the population an equal chance of being selected.

Random sampling

100

The process of conducting a survey to collect data for the entire population is called a census.

True

200
Sample
What is a part of the population
200

What is the speed of runners

QUAN

200
kids with A's, kids in Overbrook
A's(s), kids in Overbrook (p)
200

This occurs when a sample over-represents one group, leading to conclusions that cannot be generalized to the population.

Sampling Bias

200

The purpose of statistics is to prove specific outcomes

False

300
What is statistics
What is the study of data
300
How friendly are baby bulls
What is QUAL
300

teachers,  teachers in DHS 

teachers (s), teachers in DHS(p)

300

A sampling technique used when the population is divided into subgroups, and samples are taken proportionally from each group.

Stratified Sampling

300

Every statistical method can be used regardless of what type of data measurement you have (nominal, ordinal, interval, etc)

False

400
What is data
What is information that we can use
400
The attitudes of teenagers in middle school
What is QUAL
400
books in the library, all comedies
What is books in the library (p), all comedies (s)
400


The small difference between a sample statistic and the true population parameter is called this.


Sampling Error

400

Statistical Inference is a process of making estimates and testing hypotheses about the characteristics of a population

True

500
Qualitative Observations
What are observations by using words/senses
500
The reaction of train riders on a 10 hr trip
What is QUAN
500

Baby boys, baby boys that only cry during the evening

Baby boys(p), baby boys that only cry during the evening (s)

500

In this scenario, a teacher surveys only the front row of students about their test scores and concludes the entire class did well.

Biased sample

500

You should always take very small samples. That way you have less data to have to enter and work with!

False, WHY?