Chapter 1 Textbook Definitions

Definition: Statistics

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

Definition: Population

the set of all individuals of interest in a particular study —> the target demographic

Definition: Sample

a set of individuals selected from population, usually intended to represent the population in a research study —> they participate in the study

Definition: Variable

characteristic or condition that changes or has different values for different individuals

Definition: Data

measurements or observations —> collection of measurements or observations

Definition: Datum

a singular measurement or observation (AKA score, raw score)

Definition: parameter

a value, usually numerical, that describes a population —> derived from measurements of individuals in the population

Definition: a statistic

a value, usually numerical, that describes a sample —> derived from measurements of the individuals in the sample

Definition: Descriptive statistics

statistical procedures used to summarize, organize, and simplify data —> often in form of table/graph/averages

Definition: Inferential statistics

techniques that allow us to study samples and then make generalizations about the popuations from which they were selected

Definition: Sampling Error

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

Definition: Margin of Error

the predicted sampling error —> the way in which the sample differs form the population

Definition: Correlational Method

two different variables are observed to determine whether there is a correlational relationship between them (remember: correlation does not equal causation)

What is Descriptive Research

research conducted for describing individual variables as they exist naturally (eg. university student’s study habits —> just the one variable: study habits)

In a correlational study, how many variables are being analyzed and how many groups are involved

1 group —> everyone in the group is being individually assessed for 2 dependent variables (eg. sleep habits and academic performance —> are these variables related in one person)

• gets 2 scores from each participant

what type of graph/descriptive statistics is best for correlational studies

a scatter plot for numerical data (eg. number of hours studying) or a summary table for non-numerical data

what statistical test is used for evaluating the relationship between two non-numerical (i.e. categorical) variables

using Chi-square test

are correlational studies experimental or non-experimental

non-experimental —> there is no manipulation of any variable

• meaning, cannot claim causation from a correlational study

what is the main goal of experimental method

demonstrate a cause and effect relationship between two variables

how many groups and variables used in experiemental method

generally 2 groups and 2 variables. 1 Variable describes the groups (independent variable - eg. violent video games [violent game group and non violent game group]). Other variable is measured in participants (dependent variable - eg. aggresive behaviour → measured in all participants to look for difference btw groups)

what are the 2 distinguishing characteristics of the experimental method

1) researcher manipulates one variable by changing value from one level to another

2 researcher controls research situation by ensuring that there are no extraneous variables influencing the relationship being examined

what are the 2 types of variables that researchers must control for in an experimenatl method

1) participant variables: age, gender, intelligence that vary form one person to another

2) Environmental variables: lighting, time of day, and weather conditions

what are 3 things researchers can do to ensure they control variables and ensure each group is exactly same except for one dependent variable in experimental study

1) random assignment: sorting people into experimental vs control groups randomly

2) matching: making sure equal proportions in each group by choosing participants

3) Holding a certain variable constant (eg. choosing one age group only)

control condition vs experimental condition

different groups. Control condition group does not receive tretament, or may be given placebo so they think they did get treatment. Experimental condition was administered the real treatment being studied.

• purpose: providing a baseline with which can compare experimental condition

what is a nonexperimental/quasi-experimental method

when you are unable to manipulate the indpendent variable, but everything else follows typical experimental procedure

• Cannot make causal claims

what are 2 types of nonexperimental studies

1) Nonequivalent groups study

2) Pre-post study

what is a nonequivalent group study

when the researcher cannot control which participants go into which group because the groups are preexisting. Cannot have random assignment to ensure equivalent groups (eg. Age studies, cannot manipulate age variable)

what is a pre-post study

when 2 groups of scores are obtained by measuring the same variable twice for eacbh participant —> once before and once after treatment

• researcher cannot control passage of time (which is the independent variable here)

• there is confounding variable here: changes from time 1 to time 2 can be due to treatment OR can simply be due to the passage of time

what is the independent variable in a nonexperimental study called

a quasi-independent variable

what are constructs?

these are theoretic concepts/internal attributes or characteristics that cannot be directly observed but are useful for describing and explaining behaviour (eg. confidence)

what are operational definitions

a definition specifying the measurement procedure for measuring an external behaviour that also happens to measure the hypothetical constructs

(eg. a self report for how often a couple does things together → measures relationship satisfaction)

what are discrete variables

separate indivisible categories

• they cannot be divided into smaller catgeories (eg. number of children)

• eg. nominal scale data and ordinal scale

what are continuous variables

variables that contain an infinite number of possible values between any two observed values —> divisible into an infinite number of fractional parts

• eg. interval scale and ratio scale

what are real limits

for continuous vairables, each measurement category is actually an interval that must have defined boundaries

• these are these boundaries of intervals

• separeates 2 adjacent scores at exactly halfway point

• eg. the score of 170cm, has real limit of 169.5-170.5

  • 0.5 added or subtracted on the measured score

what is upper real limit and lower real limit

upper real limit = top boundary of real limit

lower real limit = lower boundary of real limit

what is a nominal scale

consists of a set of categories that have different labels → there is no quantitative distinction between the catgeories

• each category is unrelated

what is ordinal scale

set of categories that are organized into an ordered sequence 

• the categoris are ranked in size or magnitude 

• we don’t know by how much one catgeory is larger than the other though → no even quantitative distinction (eg. olympic medals)

what is interval scale

ordered categories that are all intervals of exactly the same size

• equal different btw numbers on scale reflects equal differences in magnitiude

• arbitrary zero point

• eg. temperature, IQ

What is a ratio scale

exactly the same as an interval scale BUT there is a real absolute zero point

• zero really means there is nothing

what does X mean in stat notation

X = an individual measurement/score obtained by participant

What does N mean in statistical notation

the number of scores in a population

what does n mean in statistical notation

the number of scores in a data set for a sample

what does Σ mean in stat notation

stands for “the sum of”

eg. ΣX = the sum of the scores

where does sigma fall in terms of PEDMAS

PEDM(sigma)AS

what do you do for ΣX

add up all the scores in a data set 

what do you do for ΣX²

square each score in a data set then add up the squared scores

what do you do for (ΣX)²

add up all the scores as usual then square the sum of all scores