Exam 2 Terminology

Question 1

All members of a specified group.

Answer 1

Population

Question 2

A subset of a population.

Answer 2

Sample

Question 3

Used to describe the basic characteristics of the data in a study. They provide simple summaries about the sample being measured. They can be expressed in numerical and/or graphical form. They form the basis of virtually every quantitative analysis of data.

Answer 3

Descriptive statistics

Question 4

Used to draw conclusions about a population based on information contained in a sample. Information is obtained from a sample and generalized to a population.

Answer 4

Inferential statistics

Question 5

Are used to draw conclusions about a population based on information contained in a sample. Information is obtained from a sample and generalized to a population.

Answer 5

Inferential statistics

Question 6

A value, or quantity, that represents a characteristic of a population such as the population mean or standard deviation.

Answer 6

Parameter

Question 7

A value, or quantity, that represents a characteristic of a sample such as the sample mean or standard deviation.

Answer 7

Statistics

Question 8

Something that can take on more than one value. A variable might be expected to vary over time. Values of a variable would probably be expected to differ between individuals.

Answer 8

Variable

Question 9

The various values that a variable may assume. For example, red, white, and blue are among the levels of the variable “color.” Levels of the variable “G.P.A.” include: 2.5, 3.2, and 4.0.

Answer 9

“Levels” of a variable

Question 10

A variable whose levels are described numerically. Examples include temperature, % body fat, and time.

Answer 10

Quantitative variable

Question 11

A variable whose levels are described with words or phrases. Examples include color (red, white, blue), gender (female, male), and size (small, medium, large).

Answer 11

Qualitative variable

Question 12

A quantitative variable that can be reduced to an infinite number of possible values, depending on the accuracy of the measuring instrument. Examples include height, weight, and distance.

Answer 12

Continuous variable

Question 13

A variable, either qualitative or quantitative, with a finite number of levels that cannot be subdivided meaningfully. Examples include heart rate, IQ, and color.

Answer 13

Discrete variable

Question 14

Variables are categorical, qualitative, and discrete in nature. Although numbers can be used to represent levels of the variables, the numbers are treated as labels. Examples include brand of shoes, Social Security number, and gender.

Answer 14

Nominal Level of Measurement

Question 15

Variables are categorical and discrete in nature. Unlike variables at the nominal level, variable levels at the ordinal level of measurement can be rank-ordered meaningfully. Examples include finish position in a race (1st, 2nd, 3rd, . . .) and t-shirt size (S, M, L, XL).

Answer 15

Ordinal Level of Measurement

Question 16

Variables at this level may be quantitative or qualitative, discrete or continuous. They possess the characteristics of ordinal level variables with the added characteristic of equal intervals between levels. Examples include temperature (F), shoe size, and IQ.

Answer 16

Interval Level of Measurement

Question 17

Ratio level variables possess all of the characteristics of interval level variables with the added characteristic of a measurement baseline. This baseline represents a zero point on the measurement scale or an absolute absence in quantity of the variable being measured. Examples, measured quantitatively, include height, weight, and distance.

Answer 17

Ratio Level of Measurement

Question 18

The outcome measure; the variable that is measured in a research study. It is free to vary and is affected by, or “dependent” on, the actions of other variables such as the independent variable(s).

Answer 18

Dependent variable

Question 19

A variable that you identify as having a potential influence on your outcome measure. This might be a variable that you control, like a treatment. It also might represent a demographic factor like age or gender.

Answer 19

Independent variable

Question 20

A random sample is drawn in such a way that all members of the population have an equal chance of being selected. This type of sampling is rarely used in research with human subjects.

Answer 20

Random sample

Question 21

A biased sample is drawn in such a way that some members of the population are more likely to be chosen than others.

Answer 21

Biased sample

Question 22

A convenience sample is drawn from an “intact class” or by asking people to volunteer. The sample is not randomly chosen and is typically used because of the ready availability of the subjects. This is a biased sample.

Answer 22

Convenience sample

Question 23

A sample chosen from a population that has been subdivided based upon predetermined characteristics such as gender, race, and socio-economic status. This is the sampling method used for many nationwide polls.

Answer 23

Stratified sample

Question 24

A sample obtained using a pre-determined system (not random); for example, choosing every 10th subject from the population.

Answer 24

Systematic sample

Question 25

The degree to which the experimental results can be generalized to the target population. The highest degree of external validity exists when all responses from subjects in the sample can be seen in the population. For example, an average loss of 10 pounds in the sample would be mirrored by an average loss of 10 pounds in the population.

Answer 25

External validity

Question 26

The degree to which changing the level of the independent variable causes a change in the dependent variable. In an experiment, the highest degree of internal validity exists when all fluctuations in the dependent variable can be attributed to the effect of the independent variable.

Answer 26

Internal validity

Question 27

The Avis effect occurs when subjects in a control group discover they are in a control group and they react by “trying harder.” This is a threat to the internal validity of a study.

Answer 27

Avis Effect

Question 28

The measurable, observable, or felt improvement in health or behavior not attributable to a medication or treatment that has been administered.

Answer 28

Placebo Effect

Question 29

The Hawthorne effect occurs when subjects in a treatment group improve their performance because they are aware they are being treated or tested. This is a threat to the internal validity of a study.

Answer 29

Hawthorne Effect

Question 30

A study in which the subject does not know whether he or she is in the treatment or control group.

Answer 30

Single-blind study

Question 31

The Rosenthal effect occurs when a researcher inadvertently influences subjects’ performances, which consequently affects the outcome of a study. This is a threat to the internal validity of a study.

Answer 31

Rosenthal Effect

Question 32

A study in which neither the subject nor the experimenter knows to which group the subject has been assigned.

Answer 32

Double-blind study

Question 33

The arithmetic average of a set of scores.

Answer 33

Mean

Question 34

The middle point in a set of scores.

Answer 34

Median

Question 35

The most frequently occurring score in a set of scores.

Answer 35

Mode

Question 36

A measure of variability around the mean. The standard deviation is in the same units of measurement as the mean. For example, if the mean represents average time in seconds, the standard deviation represents variability in seconds.

Answer 36

Standard deviation

Question 37

A measure of variability representing the distance from the highest score to the lowest score.

Answer 37

Range

Question 38

Skewness is a characteristic of an asymmetrical distribution. A distribution is “negatively” skewed when a higher frequency of scores are found above the mean than below it. A distribution is “positively” skewed when a higher frequency of scores are found below the mean than above it

Answer 38

Skewness

Question 39

The relative flatness or “peakedness” of a distribution. A relatively flat distribution is called “platykurtic” while a relatively peaked distribution is called “leptokurtic.”

Answer 39

Kurtosis