Data Management

Question 1

collection of information about a population which is a group of living and/or nonliving objects

Answer 1

Data

Question 2

Mathematical body of science that pertains to the collection, analysis, interpretation or explanation, and presentation of data

Answer 2

Statistics

Question 3

aspects or properties of the population that may vary across different members of the population

Answer 3

Variability

Question 4

measured numerically, involving numbers that make sense to perform arithmetic with

Answer 4

Quantitative variable

Question 5

Type of quantitative variable:
there is a gap between any two possible values of the variable

Answer 5

Discrete variability

Question 6

Type of quantitative variable:
theoretically, given any two possible values of the variable, there are other possible values between them

Answer 6

Continuous variability

Question 7

places the members of the population into groups or categories; not quantitative

Answer 7

Qualitative variable

Question 8

Type of qualitative variable:
there is a logical, natural, standard ordering of the possible values of the variable

Answer 8

Ordinal variable

Question 9

Type of qualitative variable:
there is NO logical, natural, standard ordering of the possible values of the variable, with the respect to the actual values themselves

Answer 9

Nominal variable

Question 10

used to refer to set of all objects, nonliving or living, under study

Answer 10

Population

Question 11

number of elements in population

Answer 11

population size

Question 12

subset of population

Answer 12

sample

Question 13

number of elements in sample

Answer 13

sample size

Question 14

Gathering data from sample and using math to derive conclusion about population

Answer 14

Inferential Statistics

Question 15

process of selecting a group of elements from a population

Answer 15

Sampling

Question 16

Type of Sampling:
Random Selection techniques that are used to select sample

Answer 16

Probability sampling

Question 17

Type of Sampling:
Non-random selection techniques based on certain criteria are used to select sample

Answer 17

Non-Probability sampling

Question 18

Type of probability sampling:
Randomly selecting elements from population; equal chance of getting chosen

Answer 18

Simple random sampling

Question 19

Type of probability sampling:
Selection of members at a regular interval

Answer 19

Systematic sampling

Question 20

Type of probability sampling:
division of population with similarities (homogenous) and using another probability sampling to gather sample

Answer 20

Stratified sampling

Question 21

Type of probability sampling:
Division of population regardless of similarities (heterogenous) and sample will consist of elements in selected groups only

Answer 21

Cluster sampling

Question 22

Type of non-probability sampling:
selecting easily accessible and available elements but sample may not be representative of population

Answer 22

Convenience sampling

Question 23

Type of convenience sampling:
for human population, gathering data from those willing to participate

Answer 23

Voluntary Response

Question 24

Type of non-probability sampling:
Using expertise and judgement to select sample that is best fit for the study. used in small populations to find about a phenomenon and not make statistical inferences

Answer 24

Purposive sampling

Question 25

Type of non-probability sampling: Participants in the sample recruit other participants for the study

Answer 25

Snowball sampling

Question 26

process of organizing, summarizing, and/or describing data sets. Can be used for population or sample

Answer 26

Descriptive statistics

Question 27

Type of descriptive statistics: observations or measurements about a single variable

Answer 27

Univariate data

Question 28

Type of descriptive statistics: consists of observations or measurements about two or more variables

Answer 28

Multivariate data

Question 29

Misleading data: Skewing of how data is perceived by making the baseline a different number; truncated graph

Answer 29

Omitting the baseline

Question 30

Misleading data: expanding or compressing scale on graph to make data seem more or less significant then they actually are

Answer 30

manipulating the y-axis

Question 31

Misleading data: writers only include certain data points on their graphs to reinforce their narratives creating false impression of the data

Answer 31

Cherry picking data

Question 32

Misleading data: Using wrong type of graph to skew data.

Answer 32

Using the wrong graph

Question 33

Misleading data: overtime, we have developed standards for how data is visualized, flipping those conventions can make graphs confusing to readers

Answer 33

Going against conventions

Question 34

Type of measure of centrality: average of data

Answer 34

Mean

Question 35

Type of measure of centrality: Middle value

Answer 35

Median

Question 36

Type of measure of centrality: Most frequent value

Answer 36

Mode

Question 37

Type of measure of variability: Highest value subtracted by Lowest value

Answer 37

Range

Question 38

Type of measure of variability: how dispersed data is in relation to mean

Answer 38

Standard deviation and variance