Chapter 1: Collecting Data - Sampling from a Population

Flashcards covering key concepts from lecture notes on collecting data, including definitions of population, sample, statistical inference, and different types of bias and sampling methods.

What is a population in statistics?

A population includes all individuals or objects of interest.

What is a sample in statistics?

A sample is a subset of a population.

If an angler records the weight of 12 trout he catches to estimate the size of trout in a lake, is this data considered a population or a sample?

A sample.

What is statistical inference?

It is the process of using data from a sample to gain information about its population.

What is sample bias?

Sample bias occurs when selecting a sample causes it to differ from the population in a relevant way, which usually does not yield great statistical inferences.

What was the population in the context of the 1948 Chicago Tribune "Dewey defeats Truman" headline error?

All voting Americans.

How did sample bias contribute to the Chicago Tribune's incorrect prediction of the 1948 election?

The telephone poll sample was not representative of all Americans, as predominantly wealthier individuals with phones participated, who were more likely to support Dewey.

What is a simple random sample?

A simple random sample occurs when each member of the population has an equal chance of being selected.

What is bias in data collection?

Bias is when the method of collecting data causes the sample data to be an inaccurate reflection of the population.

If you ask a random sample of students at the library about their study hours to estimate the average for all college students, is this a random sample and is the method biased?

No, it's not a random sample and the method is biased, likely giving an inflated average.

In a survey about smartphone users, if 800 participants are included, what defines the sample and the intended population?

The sample is the 800 participants, and the intended population is all US smartphone users.

In a survey about food delivery app usage, what are the 'cases' and what type of variables are "whether or not they use the app" and "which app they use"?

The cases are the people answering the survey; both variables ('whether or not they use' and 'which app they use') are categorical.

Why would a study advertised on rock radio stations for volunteers in Sydney not yield a random sample of the general population?

Because only people who listen to rock radio stations in Sydney and are willing to volunteer would participate, leading to a non-random and potentially biased sample.