OpenStax - Ch. 1 Sampling and Data

Question 1

Average

Answer 1

also called mean; a number that describes the central tendency of the data.

Question 2

Blinding

Answer 2

not telling participants which treatment a subject is receiving.

Question 3

Categorical Variable

Answer 3

variables that take on values that are names or labels.

Question 4

Cluster Sampling

Answer 4

a method for selecting a random sample and dividing the population into groups (clusters); use simple random sampling to select a set of clusters. Every individual in the chosen clusters is included in the sample.

Question 5

Continuous Random Variable

Answer 5

a random variable (RV) whose outcomes are measured; the height of trees in the forest is a continuous RV.

Question 6

Control Group

Answer 6

a group in a randomized experiment that receives an inactive treatment but is otherwise managed exactly as the other groups.

Question 7

Convenience Sampling

Answer 7

a nonrandom method of selecting a sample; this method selects individuals that are easily accessible and may result in biased data.

Question 8

Cumulative Relative Frequency

Answer 8

The term applies to an ordered set of observations from smallest to largest. The cumulative relative frequency is the sum of the relative frequencies for all values that are less than or equal to the given value.

Question 9

Data

Answer 9

a set of observations (a set of possible outcomes); most data can be put into two groups: qualitative (an attribute whose value is indicated by a label) or quantitative (an attribute whose value is indicated by a number). Quantitative data can be separated into two subgroups: discrete and continuous. Data is discrete if it is the result of counting (such as the number of students of a given ethnic group in a class or the number of books on a shelf). Data is continuous if it is the result of measuring (such as distance traveled or weight of luggage)

Question 10

Discrete Random Variable

Answer 10

a random variable (RV) whose outcomes are counted.

Question 11

Double-blinding

Answer 11

the act of blinding both the subjects of an experiment and the researchers who work with the subjects.

Question 12

Experimental Unit

Answer 12

any individual or object to be measured.

Question 13

Explanatory Variable

Answer 13

the independent variable in an experiment; the value controlled by researchers.

Question 14

Frequency

Answer 14

the number of times a value of the data occurs.

Question 15

Informed Consent

Answer 15

Any human subject in a research study must be cognizant of any risks or costs associated with the study. The subject has the right to know the nature of the treatments included in the study, their potential risks, and their potential benefits. Consent must be given freely by an informed, fit participant.

Question 16

Institutional Review Board

Answer 16

a committee tasked with oversight of research programs that involve human subjects.

Question 17

Lurking Variable

Answer 17

a variable that has an effect on a study even though it is neither an explanatory variable nor a response variable.

Question 18

Nonsampling Error

Answer 18

an issue that affects the reliability of sampling data other than natural variation; it includes a variety of human errors including poor study design, biased sampling methods, inaccurate information provided by study participants, data entry errors, and poor analysis..

Question 19

Numerical Variable

Answer 19

variables that take on values that are indicated by numbers.

Question 20

Parameter

Answer 20

a number that is used to represent a population characteristic and that generally cannot be determined easily.

Question 21

Placebo

Answer 21

an inactive treatment that has no real effect on the explanatory variable.

Question 22

Population

Answer 22

all individuals, objects, or measurements whose properties are being studied.

Question 23

Probability

Answer 23

a number between zero and one, inclusive, that gives the likelihood that a specific event will occur.

Question 24

Proportion

Answer 24

the number of successes divided by the total number in the sample.

Question 25

Qualitative Data

Answer 25

an attribute whose value is indicated by a label.

Question 26

Quantitative Data

Answer 26

an attribute whose value is indicated by a number.

Question 27

discrete (quantitative) data

Answer 27

(subgroup) Data is discrete if it is the result of counting (such as the number of students of a given ethnic group in a class or the number of books on a shelf).

Question 28

continuous (quantitative) data

Answer 28

(subgroup) Data is continuous if it is the result of measuring (such as distance traveled or weight of luggage.)

Question 29

Random Assignment

Answer 29

the act of organizing experimental units into treatment groups using random methods.

Question 30

Random Sampling

Answer 30

a method of selecting a sample that gives every member of the population an equal chance of being selected.

Question 31

Relative Frequency

Answer 31

the ratio of the number of times a value of the data occurs in the set of all outcomes to the number of all outcomes to the total number of outcomes.

Question 32

Representative Sample

Answer 32

a subset of the population that has the same characteristics as the population

Question 33

Response Variable

Answer 33

the dependent variable in an experiment; the value that is measured for change at the end of an experiment.

Question 34

Sample

Answer 34

a subset of the population studied.

Question 35

Sampling Bias

Answer 35

not all members of the population are equally likely to be selected.

Question 36

Sampling Error

Answer 36

the natural variation that results from selecting a sample to represent a larger population; this variation decreases as the sample size increases, so selecting larger samples reduces sampling error.

Question 37

Sampling with Replacement

Answer 37

Once a member of the population is selected for inclusion in a sample, that member is returned to the population for the selection of the next individual.

Question 38

Sampling without Replacement

Answer 38

A member of the population may be chosen for inclusion in a sample only once. If chosen, the member is not returned to the population before the next selection.

Question 39

Simple Random Sampling

Answer 39

a straightforward method for selecting a random sample; give each member of the population a number. Use a random number generator to select a set of labels. These randomly selected labels identify the members of your sample.

Question 40

Statistic

Answer 40

a numerical characteristic of the sample; a statistic estimates the corresponding population parameter.

Question 41

Stratified Sampling

Answer 41

a method for selecting a random sample used to ensure that subgroups of the population are represented adequately; divide the population into groups (strata). Use simple random sampling to identify a proportionate number of individuals from each stratum.

Question 42

Systematic Sampling

Answer 42

a method for selecting a random sample; list the members of the population. Use simple random sampling to select a starting point in the population.

Let k = (number of individuals in the population)/(number of individuals needed in the sample). Choose every kth individual in the list starting with the one that was randomly selected. If necessary, return to the beginning of the population list to complete your sample.

Question 43

Treatments

Answer 43

different values or components of the explanatory variable applied in an experiment.

Question 44

Variable

Answer 44

a characteristic of interest for each person or object in a population.