Stats 4 Psych: Prep for Exam 1: Chapters 1-2

Population

Complete set of individuals having some common observable characteristics

Parameter

A number that describes an entire population (unreaslistic in real life testing)

Statistic

Uses a small sample to infer data about a larger population

Measurement Metrics for Parameter

Mean, SD, correlation (p) (greek letters)

Measurement metrics for statistic

Mean, SD, correlation (r )

Two types of Statistics

Descriptive and inferential

Descriptive statistics

Directly describe your sample ex. Mean, median, mode

Inferential statistics

Numbers used based on data to draw conclusion/ like p being used as correlation

Representative Psychology

Not representative bc. Psychology is more fluid and evolving- too many variables

Measurement Definition

A system for assigning numerical values to observations in a consistent and reproducible way

Nominal scale

Values are categorical and do not have any relation to each other. Numbers assigned to nominal scale do not have any value

Dichotomous variable

Only two options

Ordinal scale

Numbers have meaning relative to eachother but spacing within order is not standardized

Interval

Values are evenly spaced apart (temperature)

Ratio

Values are seen are proportional to eachother, and contains notion of absolute zero.

Continuous vs discrete

One variable is countable one is infinite

Likert Scale

Commonly used in questionnaire: strongly disagree-strongly agree

Bar vs Histogram Graphs

Bar must be discrete/categorical (nominal) ex. Population size, while histogram can give slight range ex. Height from 5ft to 5ft1

Frequency polygon

Similar to histogram in the sense that you connect to dots at the peak instead of putting continuous bars

Cumulative frequency polygon (OGIVE)

Adds up frequencies to make continuously growing frequency polygon of percentage

Normal distribution

Most commonly assumed for psychological statistics

Features of Normal distribtution

1) singe mode, 2) symetrical, 3) extends to infinity

Shapes of frequency

Skewed right= pos skewed, and skewed left= neg skewed.

Ceiling effect

When data piles up at top end

Floor effect

When data piles at low end of distribution

KURTOTIC distribution

Extreme versions of normal (condensed vertically or horizontally)

Leptokurtotic distribution

Tall and skinny

Platykurtotic distribution

Flatter with skinnier tails

Central tendencies

There is not one singular point that marks the center of a set of data

Semi interquatrile range (SIG) formula

(Q3-Q1)/2

Mean deviation formula

(Sum of distance from all points minus mean)/ number of scores

Variance

(Take the square of all deviations for each data point from the mean)/ number of data points

SD

Square root of variance

Symmetric distribution

Mode=median

Postivey skewed distribution

Mode<Mean

Negatively skewed distribution

Mode>Mean

Properties of mean

Add and subtract to data: apply same to mean. Multiply/divide data points: same applies to mean

Properties of Standard Deviation

If constant is added/subracted: not affected. If multiplied and divided by constant: same applies to SD