Introduction to Statistics - Lecture Flashcards

Flashcards covering key topics from the lecture notes: statistics basics, populations and samples, research methods, variable types, and scales of measurement.

What is statistics?

Statistics are the mathematical procedures used to organize, summarize, and interpret information; a branch of mathematics devoted to collecting, analyzing, interpreting, and presenting data.

Why is statistics important?

It helps the researcher answer questions that initiated the research.

What is a population?

The set of all individuals of interest in a particular study; often very large.

What is a sample?

A subset of individuals selected from a population; usually intended to represent the population.

In the population–sample relationship, what is generalized from the sample?

The results from the sample are generalized to the population.

What is a population parameter?

A measurable quality of the population (e.g., population mean μ, population standard deviation σ).

What is a sample statistic?

A measurable quality of the sample (e.g., sample mean M, sample standard deviation s).

What are Descriptive Statistics?

Statistics that organize, summarize, and describe data (e.g., graphs; measures of central tendency).

What are Inferential Statistics?

Statistics that generalize from samples to populations; involve hypothesis testing and making inferences (e.g., t-tests, ANOVAs).

What is sampling error?

The natural differences between a sample statistic and the population parameter due to chance.

What are the steps in the research process?

Research question, form a hypothesis, design study, collect data, analyze data, draw conclusions, report findings.

What is the goal of the Experimental Method?

To demonstrate a cause-and-effect relationship; requires manipulation of the IV, random assignment, and a control group.

What is manipulation in an experiment?

Changing the value of the independent variable from one level to another.

What is a control condition?

A baseline condition where participants do not receive the experimental treatment (or receive a neutral/placebo treatment).

What is random assignment?

Each participant has an equal chance of being assigned to each treatment condition.

What is the purpose of a control group?

To provide a baseline for comparison with the experimental group.

What are participant variables?

Characteristics that vary from person to person (e.g., age, gender, education level, IQ).

What are environmental variables?

Environmental factors such as lighting, time of day, background noise.

What are extraneous variables?

Variables not of interest but could influence the dependent variable.

What is an operational definition/operationalization?

Defines a construct in terms of observable and measurable behaviors (e.g., aggression measured as number of punches on a bag).

What is a nonexperimental study?

A study with non-equivalent groups where random assignment is not possible (quasi-experimental design).

What is a quasi-independent variable?

The variable used to create groups in a nonexperimental study; not manipulated by random assignment.

What is a discrete variable?

Consists of separate, indivisible categories; values in whole units (e.g., number of children, siblings, pets).

What is a continuous variable?

Contains an infinite number of possible values between observed values; measured on a continuum (e.g., height, weight).

What are the four scales of measurement (NOIR)?

Nominal, Ordinal, Interval, Ratio.

Nominal scale characteristics?

Non-numerical, categorical; examples: brand, degree type; no quantitative distinctions.

Ordinal scale characteristics?

Ordered categories with magnitude but not equal differences; examples: race results, rating scales.

Interval scale characteristics?

Ordered categories with equal intervals; no true zero point; examples: Celsius temperature, IQ.

Ratio scale characteristics?

Ordered categories with equal intervals and a true zero point; examples: number of correct answers, time, weight, height.

Which NOIR scale has a true zero point?

Ratio.

What does margin of error refer to?

The natural difference between a sample statistic and the corresponding population parameter.

What is a representative sample?

A sample that accurately represents the population.

What is the difference between a population parameter and a sample statistic?

Parameter is a population value; statistic is a sample estimate.

What is the difference between descriptive and inferential statistics?

Descriptive statistics describe and summarize data; inferential statistics generalize to populations and test hypotheses.