# Chapter 1 (Woods ver.)

## 28 terms

### Statistics

pieces of information presented in numerical form; this includes pictures (e.g. graphs, figures) too

### Population

the entire set of all possible occurrences; can be broad or narrow

### Sample

a subset of a population; often a subset selected for study - ideally, it closely resembles the population

### Accurate sampling

sample statistics are similar to the population parameter

### Inaccurate sampling

due to sampling error

### 2 broad categories of statistics

Descriptive and inferential

### Descriptive statistics

Organize and summarize information

### Inferential statistics

Make generalized statements about a population; test hypotheses - experiments rely on these

### The scientific method

A systematic way of gathering and interpreting observations

### 2 categories of observations

Variables (can change); constants (do not change)

### Sampling

How participants are selected - ideally random sampling is used

### Random assignment

Placing participants into groups - experimental group and control group

### 2 types of variables

Independent and dependent

### Independent variables

manipulations; the treatment

### Dependent variables

measurements; the data

### Qualitative variables

e.g. names; usually non-numerical

### Quantitative variables

e.g. exam scores; have numerical values

### Discrete variables

Change in finite steps; often described with integers (e.g. number of students)

### Continuous variables

Fall on an infinitely fine-grained scale; can be described with real numbers (e.g. reaction time)

### Types of experiments

"True"; quasi-experimental; correlational

### "True" experiments

Random sampling and assignment; manipulation of variables

### Quasi-experimental experiments

Random selections but NO random assignment

### Correlational methods

No experimental manipulation; investigate the relationships between variables

### 4 data scale types

Nominal; ordinal; interval; ratio

### Nominal scale

Described by name or type only; frequency-of-occurrence; no information about order or magnitude - Categorical

### Ordinal scale

Can put data into orders or ranks; relative placement (no information about magnitude); e.g. order in which people finish a problem-solving task

### Interval scale

Convey information about differences between numerical observation; relative magnitude (equal size intervals assumed); no information about absolute magnitude; e.g. thermometer

### Ratio scale

Absolute zero point; can be described with ratios; convey information about absolute magnitude; e.g. all physical measures