PsychStats

Psychology

scientific study of human behavior and mental processes

Goals of Psychology

Describe, Predict, Explain, and Control

Statistics

a set of mathematical procedures for organizing, summarizing, and interpreting information

Population

This is the entire set of items from which you draw data for a statistical study

Parameter

A number describing a whole population

Sample

The specific group in which data may be collected from

Statistic

A number describing a sample

Variable

A person , place, thing, or phenomenon that researchers are trying to measure

Values

possible number or category that a score can have

Score

raw score, is a particular person's value on a variable

Data (plural)

-are measurements or observations.
-a single measurement or observation and is commonly called a score or raw score.
-Datum (singular)

Data Set

a collection of measurements or observations

Descriptive Statistics

A type of statistics that DESCRIBES, SHOWS, and SUMMARIZES the basic features of a data set found in a given study, presented in a summary that describes that data sample and its measurements.

Inferential Statistics

A type of statistics that has a goal of making GENERALIZATION about a population

Sampling Error

The naturally occurring discrepancy, or error, that exists between a sample statistic and the corresponding population parameter

Discrete Variable

-consists of separate, indivisible categories.
-E.g. (number of students, number of correct answers)

Continuous Variable

-there are an infinite number of possible values that fall between any two observed values.
-E.g. Speed, Height, Weight, Temperature

Dichotomous Variable

These are variables which only have two categories or levels

Artificial Dichotomous

derived from scores (e.g. passed/failed)

True Dichotomous

naturally occurring (Male/Female, Yes/No, True/False, Heads/Tails)

Levels of Measurement

also called as scales of measurement, is a classification that describes the nature of information within the values assigned to variables

Nominal

-a variable with values that are categories
-also known as categorical variables
-E.g. Sex, Nationality, Religion, Civil Status

Ordinal

-numeric variable in which the values are ranks
-also known as rank-order variable
-E.g. Clothing Sizes (S, M, L, XL), Class Rank, Grades (A - F), Level of Self-Confidence (Low, Average, High), Likert Scale

Interval

-the variable that contains equal intervals between numbers and contains no absolute zero point.
-E.g. Temperature (Fahrenheit and Celsius), IQ, Stress

Ratio

-an interval scale with the additional feature of an absolute zero point
-E.g. Time to complete a task, number of correct answers, weight gain in the past 6 months

Nominal

What is your favorite color?

Nominal

What is your student number

Interval

Temperature in celsius

Ordinal

Service quality rating

Interval

Temperature in fahrenheit

Ratio

How much do you weigh?

Ordinal

Top 10 best song in Spotify

Nominal

What is your name?

Ordinal

Level of stress

Nominal

Jersey number

Ratio

Number of sales made

Ordinal

Your rank in class

Nominal

Home address

Ratio

Daily allowance in school

Ratio

Amount of money

Nominal

Religion

Ordinal

Rate your satisfaction level

Nominal

Yes or No

Descriptive Research

or the descriptive research strategy, involves measuring one or more separate variables for each individual with the intent of simply describing the individual variables

Survey Research

a useful way of obtaining data about people's opinions, attitudes, preferences, and experiences that are hard to observe directly; data may be obtained using questionnaires and interviews

Relationship Between Variables

-two (or more) variables observed and measured
-one of two possible data structures used to determine what type of relationship exists

Correlational Method

two different variables are observed to determine whether there is a relationship between them

Correlational Method Limitations

-can demonstrate the existence of a relationship
-does not provide an explanation for the relationship
-most importantly, does not demonstrate a cause and-effect relationship between the two variables

Experimental Method

-this research design, one (or more) variable is manipulated while another variable is observed or measured
-this design aims to establish a cause and-effect relationship between the two variables and attempts to control all other variables to prevent them from influencing the results

Independent Variable

-the variable that is manipulated by the researcher
-it should consists of at least two (or more) levels (treatment conditions) to which subjects are exposed

Dependent Variable

the variable that is being observed or measured to assess the effect of the treatment

Experimental Condition

a condition in an experiment wherein the subjects will receive the experimental treatment

Control Condition

a condition in an experiment wherein the subjects do not receive the experimental treatment

Quasi-Experimental Design

often seem like (as the prefix quasi implies) real experiments, but they lack one or more of its essential elements, such as manipulation of antecedents and random assignment to treatment conditions

Nonequivalent Groups Design

a design in which the researcher compares the effect of different treatment conditions on pre-existing groups of participants

Pretest/Posttest Design

a research design used to assess whether the occurrence of an event alters behavior; scores from measurements made before and after the event

Ex-Post Facto Study

a study in which a researcher systematically examines the effects of pre-existing subject characteristics (or subject variables) by forming groups based on theses naturally occurring differences between subjects

Longitudinal Design

a method in which the same group of subjects is followed and measured at different points in time; a method that looks for changes across time

APA Format

this form of writing research papers is used mainly in the social sciences, like psychology, anthropology, sociology, as well as education and other fields

Frequency Distribution

an organized tabulation of the number of individual located in each category on the scale of measurement

Frequency Tables

ordered listing of number of individuals/subjects/respondents having each of the different values for a particular variable

Proportion

it measures the fraction of the total group that is associated with each score

Percentage

an amount of something, often expressed as a number out of 100

Grouped Frequency Table

frequency table in which the number of individuals (frequency) is given for each interval of values.

Interval

range of values in a grouped frequency table that are grouped together.

Histogram

-barlike graph of a frequency distribution in which the values are plotted along the horizontal axis and the height of each bar is the frequency of that value
-the bars are usually placed next to each other without spaces, giving the appearance of a city skyline

Frequency Polygon

continuous line that represents the frequencies of scores within a class interval, based on a histogram; used for continuous data

Column Chart

a data visualization where each category is represented by a rectangle, with the height of the rectangle being proportional to the values being plotted

Bar Graph

categories are organized vertically on the y-axis, and values are shown horizontally on the x-axis.

Line Graph

also known as a line plot or line chart is a graph which uses lines to connect individual data points that display quantitative values over a specified time interval

Central Tendency

-typical or most representative value of a group of scores
-Mean, Median, Mode

Mean (M)

-arithmetic average of a group of scores; the sum of the scores divided by the number of scores
-the balance point of a distribution

Weighted Mean

an average in which each observation in the data set is assigned or multiplied by a weight before summing to a single average value

Median (Mdn)

middle score when all the scores in a distribution are arranged from lowest to highest

Mode

value with the greatest frequency in the distribution

Unimodal Distribution

frequency distribution with one value clearly having a larger frequency than any other

Bimodal Distribution

frequency distribution with two approximately equal frequencies, each clearly larger than any the others

Multimodal Distribution

frequency distribution with two or more high frequencies separated by a lower frequency

Rectangular Distribution

frequency distribution in which all values have approximately the same frequency

Symmetrical Distribution

distribution in which the pattern of frequencies on the left and right side are mirror images of each other

Skewed Distribution

distribution in which the scores pile up on one side of the middle and are spread out on the other side; distribution that is not symmetrical

Positively Skewed Distribution

the peak (highest frequency) in the distribution is on the left-hand side with tail tapering off the right

Floor Effect

situation in which many scores pile up at the low end of a distribution (creating a skewness to the right) because it is not possible to have any lower score.

Negatively Skewed Distribution

the peak (highest frequency) in the distribution is on the right-hand side with the tail tapering of the left

Ceiling Effect

situation in which many scores pile up at the high end of a distribution (creating a skewness to the left) because it is not possible to have a higher score.

Normal Curve

specific, mathematically defined, bell-shaped frequency distribution that is symmetrical and unimodal; distributions observed in nature and research commonly approximates it
• also called the Gaussian Distribution

Kurtosis

extent to which a frequency distribution deviates from a normal curve in terms of whether its curve in the middle is more peaked or flat than the normal curve.

Leptokurtic

the scores are concentrated towards the mean

Mesokurtic

normal curve

Platykurtic

the scores have an extremely large deviation from the mean

Variability

provides a quantitative measure of the difference between scores in a distribution and describes the degree to which the scores are spread out or clustered together.

Purpose of Measuring Variability

-Variability describes the distribution.
-Variability measures how well an individual score (or group of scores) represents the entire distribution.

Range

-distance covered by the scores in distribution, from the smallest score to the largest score
-the difference between the largest score and smallest score

Variance

measure of how spread out a set of scores are; average of the squared deviations from the mean

Deviation or Deviation Score

the difference between a score and the mean

Standard Deviation

-square root of the average of the squared deviations from the mean; the most common descriptive statistics for variation
- approximately the average amount that scores in a distribution vary from the mean

Definitional Formula

equation for a statistical procedure directly showing the meaning of the procedure.

Computational Formula

equation mathematically equivalent to the definitional formula. Easier to use for figuring by hand, it does not directly show the meaning of the procedure

Biased Statistics

if the average value of the statistic either underestimates or overestimates the corresponding population parameter

Unbiased Statistics

if the average value of the statistic is equal to the population parameter