CH 1

Question 1

Random Variables

Answer 1

A random variable is a property that can take on different (at least 2) values (i.e., it varies). These values have associated probabilities and we can thus talk about their associated probability distributions.

symbolized as - X Y

-Not to be confused with psychological “objects” (intelligence, emotion, happiness)
Constants are fixed values that do not cary variance

Question 2

Discrete Variables

Answer 2

Discrete random variables are those that can only take on particular values that are made up of disjointed categories. (e.g. random variable X that van only take on values 1,2,3,4,5) or (e.g. X can only take on values green, blue, and red)

Question 3

Continuous Variables

Answer 3

Continuous random variables can take on values along an entire interval of the number line, and these values are not disjointed. (e.g. random variable Y that can take on values between 1 & 5 and everything in-between 1.233, 4.34 etc)

Question 4

Data

Answer 4

Numerical (or non-numerical) information collected by the researcher- these are usually observed values on random variables

Question 5

Data Matrix

Answer 5

Organizes data in an array of columns/rows with order nxp.
-n=number of rows of matrix (usually # of observations)
-p=bumber of columns of the Matrix (usually # of variables)
(n rows by p columns)

Question 6

Population versus Sample

Answer 6

Census population: All individuals or objects of interest to a researcher

Statistical Population: The entire set of possible outcomes on a variable of interest and their associated probabilities and frequencies

Sample: A subset or portion of scores or measurements taken from a population

Question 7

Parameter versus Statistic

Answer 7

Parameters: Numerical properties that describe statistical populations

Statistics: Real-valued quantities that describe various features of a data set (the sample)

Question 8

Empirical Distributions vs Theoretical Distributions

Answer 8

empirical:
-based on observed (raw) data
-the distribution of a set of scores observed on variable X.
Theoretical:
-not based on any observed data
-abstract
-theoretical distribution of scores on variable X can be constructed by mathematicians

Question 9

Data analysis vs Statistical Inference

Answer 9

D.A.:

• describing empirical distribution ( a raw data set)
• only interested in describing the data that we have collected, not making inferences about a theoretical population

S.I. :
-Calculating statistics on a sample in order to make inferences about the parameters of a population which the sample (presumably) represents.

(really need to make difference clear between population and sample when dealing with statistical inferences)