Research Design II - Quiz 1

Population

Entire group of individuals of interest

Sample

Subset selected from a population

Parameter

Numerical value describing a population

Statistic

Numerical value describing a sample

Random sampling

Chance selection of participants from a population

Random assignment

Chance placement of participants into conditions

Sampling error

Difference between a sample statistic and a population parameter

Descriptive statistics

Methods used to organize and summarize data

Inferential statistics

Methods used to draw conclusions about a population from a sample

Variable

Characteristic that can vary across individuals

Independent variable (IV)

Variable manipulated by the researcher

Dependent variable (DV)

Variable measured to assess the effect of the IV

Levels of an IV

Different conditions or values of the independent variable

Experimental design

Manipulation of an IV with random assignment

Quasi-experimental design

Manipulation of an IV without random assignment

Observational design

No manipulation of the IV

Nominal scale

Categories with no order

Ordinal scale

Categories with rank order but unequal intervals

Interval scale

Ordered categories with equal intervals and no true zero

Ratio scale

Ordered categories with equal intervals and a true zero

Discrete variable

Variable consisting of indivisible categories

Continuous variable

Variable that can take any value within a range

Frequency distribution

Table or graph showing how often each score occurs

Histogram

Graph for continuous data with touching bars

Bar graph

Graph for discrete or categorical data with separated bars

Central tendency

Statistical measure that identifies the center of a distribution

Mean

Arithmetic average of scores

Median

Score that divides a distribution so that 50% are above and 50% below

Mode

Most frequently occurring score or category

Mu (μ)

Symbol for the population mean

M

Symbol for the sample mean

N

Number of scores in a population

n

Number of scores in a sample

Σ

Summation symbol indicating addition of scores

Mean as equal distribution

The amount each individual receives when the total is divided equally

Mean as balance point

Point where distances above and below the mean are equal

Sum of deviation scores

The sum of (X − M) always equals zero

Mean range rule

The mean must fall between the lowest and highest scores

Mean sensitivity

The mean is affected by extreme scores

Median resistance

The median is relatively unaffected by extreme scores

Weighted mean

Mean that accounts for unequal sample sizes

Weighted mean rule

The overall mean is closer to the mean of the larger sample

Median (odd n)

Middle score when data are ordered

Median (even n)

Average of the two middle scores

Median location

Point on the scale where 50% of scores fall below

Lower real limit (LRL)

Lowest possible value of a score interval

Upper real limit (URL)

Highest possible value of a score interval

Precise median

Exact midpoint for a continuous variable using interpolation

fBELOW LRL

Number of scores below the lower real limit

fTIED

Frequency of tied scores at the median value

Mode requirement

The mode must correspond to an actual score

Bimodal distribution

Distribution with two modes

Major mode

Mode with the highest frequency

Minor mode

Secondary mode with a lower frequency

Symmetrical distribution

Distribution where left and right sides mirror each other

Positively skewed distribution

Distribution with a long tail to the right

Negatively skewed distribution

Distribution with a long tail to the left

Mean-median-mode (symmetric)

Mean = Median = Mode

Mean-median-mode (positive skew)

Mean > Median > Mode

Mean-median-mode (negative skew)

Mean < Median < Mode

Selecting central tendency

Choosing mean, median, or mode based on data shape and scale

Mean best use

Symmetrical distributions without extreme scores

Median best use

Skewed distributions or distributions with outliers

Mode best use

Nominal data or most frequent category