What is the purpose of studying statistics in psychology?
To become an informed consumer and producer of information. It allows psychologists to accurately interpret, analyze, and communicate data, make informed decisions, and test hypotheses objectively.
What are descriptive statistics?
Descriptive statistics organize, summarize, and present data. Examples include calculating the mean, median, mode, range, and creating graphs to describe data patterns.
What are inferential statistics?
Inferential statistics involve using sample data to make generalizations or inferences about a larger population. For example, predicting population behavior from a sample survey.
What is the difference between a population and a sample?
A population is the entire group of individuals of interest, while a sample is a smaller subset used to estimate characteristics of the population.
What is a variable in statistics?
A variable is any characteristic or property that can vary among individuals. Example: height, age, reaction time.
What is the difference between numerical and categorical data?
Numerical data consist of measurable quantities (e.g., age, income), while categorical data describe qualities or labels (e.g., gender, color).
What is the difference between univariate and multivariate data sets?
Univariate data involve one variable (e.g., test scores), while multivariate data involve two or more variables (e.g., test scores and study hours).
What are discrete numerical variables?
They take on countable, separated values (e.g., number of children, dice rolls).
What are continuous numerical variables?
They can take any value within a range (e.g., height, weight, time).
What are frequency and relative frequency?
Frequency is how often a category occurs; relative frequency is the proportion of that category relative to the total.
What is an observational study?
A study that observes individuals without manipulating variables. It identifies patterns or associations but not causation.
What is an experimental study?
A study in which one or more variables (independent variables) are manipulated to observe their effect on another variable (dependent variable).
What are common sources of bias in data collection?
Selection bias (non-representative sample), measurement bias (inaccurate tools), and nonresponse bias (missing data from certain groups).
Why is avoiding bias important?
Bias distorts findings and prevents accurate generalization about a population. Minimizing bias ensures reliability and validity of results.
What is an example of misleading statistics?
A graph showing a strong correlation that is actually spurious (e.g., ice cream sales and shark attacks). It reminds us to evaluate data critically.
