PSY201: Introduction to Quantitative Research in Psychology 1

Flashcards summarizing key information from the PSY201 course syllabus and relevant statistics concepts.

What percentage does the term test contribute to the final grade?

30%.

What is an observational study?

A study in which characteristics of a sample from one or more existing populations are observed.

What is the difference between descriptive and inferential statistics?

Descriptive statistics organize and summarize data, while inferential statistics make inferences about the population from a sample.

What is a sample?

A subset of the population from which information is collected.

What is a discrete numerical variable?

A numerical variable whose possible values are isolated and limited points on the number line.

What are the four best practices for designing good experiments?

Direct control, random assignment, blocking, and replication.

What is the function of extraneous variables in an experimental study?

They are variables not controlled by the experimenter that can affect the response variables.

What type of study is designed to observe the effects of manipulated variables?

Experimental study.

What does random sampling ensure?

Every different possible sample of size n has the same chance of being selected.

What is the penalty for not showing up on time for a SONA experiment?

A penalty of -1 credit.

What is the role of explanatory variables?

Explanatory variables are controlled or manipulated by the experimenters.

What is a recommended approach for collecting data sensibly?

Simple random sampling.

What is blocking, and Stratified Sampling, replication
How do they differ

Blocking is controlling for known variants by grouping similar characteristics together to reduce noice Eg: Age might affect the result of a study so we group the age 

Stratified Sampling is done before the experiment spliting people into categories such as age, gender, income.

Replication is repeating the experiment to gain credibility. 

What are the diffrent types of sampling 

A) Cluster Sampling

🧪 Sampling Methods Cheat Sheet

Method	How It Works	Best Used When...
A) Cluster Sampling	Randomly select entire groups (clusters), then sample everyone within them	Populations are naturally grouped (e.g., schools, cities)
B) Stratified Sampling	Divide population into subgroups (strata) based on a characteristic, then sample within each	You want proportional representation across key traits
C) Systematic Sampling	Select every kth individual from a list after a random start	You have a complete list and want a simple, evenly spaced sample
D) Convenience Sampling	Use whoever is easiest to reach (e.g., friends, passersby)	You're short on time/resources—but it risks bias

Types of data and datasets 

Types of data and datasets • Numerical data: Data whose observations are numerical. (e.g., 5’8”, 6’2”, etc) • Categorical (qualitative) data: Data whose observations are categorical (e.g., male, female, etc) • Univariate data set: A set of data whose observations vary only in one characteristics • Multivariate data set: A set of data whose observations vary in multiple characteristics