Data Literacy D772 WGU
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1. Sample: A smaller, more manageable group selected from the population to represent the larger group.
2. Sample (Example): A group of 500 high school students from different states across the U.S.
3. Population: The entire group of individuals or objects that you want to study.
4. Population (Example): All high school students in the United States.
5. What is a parameter in statistics?: A numerical value describing an entire population's characteris-
tics.
6. Is a parameter a fixed value?: Yes, a parameter is a fixed value.
7. Why is a parameter often unknown?: Because collecting data from every member of a large
population is usually impractical or impossible.
8. What is a statistic?: A numerical value that describes a characteristic of a sample.
9. How is a statistic calculated?: It is calculated from the data collected from the sample.
10. What is the purpose of using statistics?: To estimate the corresponding population parameter.
11. Statistic (Example): The average height of 100 adult women randomly selected from the United States.
12. Parameter (Example): The average height of all adult women in the United States.
13. Basic elements that make up a dataset: individuals, variables, and data.
14. Individuals: are the objects described by a set of data. people, animals, or things. What we collect information
on.
15. Variables: are the characteristics or measurements that we are interested in studying. Specific aspects of the
individuals that we collect data on. Can be either quantitative (numerical) or categorical (qualitative-Fav color, gender,
job).
16. Data: are the actual values of the variables
17. The ____ is the 100 first-year students who were randomly surveyed.
The ____ is a group of students who graduated from the university last year,
randomly selected: Sample
18. The ____ is all first-year students attending Strime University this term.
The ____ is a group of all students who graduated from the university last
year.: Population
19. The ____ is the average (mean) amount of money spent (excluding books) by
first-year university students in the sample.
The ____ is the average cumulative GPA of students in the study who graduated
from the university last year.: Statistic
, Data Literacy D772 WGU
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20. The ____ could be the amount of money spent (excluding books) by one
first-year student.
The ____ is the cumulative GPA of one student who graduated from the univer-
sity last year.: Variable
21. The ____ are the dollar amounts spent by the first-year students.
The ____ consists of the values 3.65, 2.80, 1.50, 3.90.: Data
22. The ____ is the average (mean) amount of money spent (excluding books) by
first-year university students at Strime University this term.
The ____ is the average cumulative GPA of students who graduated from the
university last year.: Parameter
23. Strata: Subgroups within a population that share a common characteristic (e.g., age group, gender, income
level).
24. Strata (Example): A high school population might be divided into strata based on grade level (freshmen,
sophomores, juniors, seniors).
25. Proportionate Sample: A sample where the number of individuals selected from each stratum is
proportional to the size of that stratum in the population.
26. Proportionate Sample (Example): If 25% of the high school population is freshmen, then 25% of
the sample should also be freshmen.
27. Stratified sampling: involves dividing the population into distinct subgroups called strata, based on
specific characteristics such as age, gender, or socioeconomic status. Once the population is divided into strata, a
random sample is taken from each stratum in proportion to its representation in the overall population. This ensures
that the sample reflects the diversity of the population in terms of the chosen characteristics
28. Cluster sampling: involves dividing the population into clusters, which are naturally occurring groups like
schools, neighborhoods, or cities. Instead of randomly selecting individuals from the entire population, researchers
randomly select a few clusters and include all individuals within those selected clusters in the sample. This method is
often used when it's difficult or expensive to sample individuals directly from the entire population
29. Cluster: A naturally occurring group within a population (e.g., school, neighborhood, city).
30. Cluster (Example): A researcher studying the opinions of high school students in a state might randomly
select five schools and survey all students within those schools.
31. Systematic sampling: involves selecting every "nth" individual from a list of the population, starting from
a randomly chosen point. This method is often used when it's easy to access a list of the entire population. It's a simple
and efficient method
Study online at https://quizlet.com/_hq99qs
1. Sample: A smaller, more manageable group selected from the population to represent the larger group.
2. Sample (Example): A group of 500 high school students from different states across the U.S.
3. Population: The entire group of individuals or objects that you want to study.
4. Population (Example): All high school students in the United States.
5. What is a parameter in statistics?: A numerical value describing an entire population's characteris-
tics.
6. Is a parameter a fixed value?: Yes, a parameter is a fixed value.
7. Why is a parameter often unknown?: Because collecting data from every member of a large
population is usually impractical or impossible.
8. What is a statistic?: A numerical value that describes a characteristic of a sample.
9. How is a statistic calculated?: It is calculated from the data collected from the sample.
10. What is the purpose of using statistics?: To estimate the corresponding population parameter.
11. Statistic (Example): The average height of 100 adult women randomly selected from the United States.
12. Parameter (Example): The average height of all adult women in the United States.
13. Basic elements that make up a dataset: individuals, variables, and data.
14. Individuals: are the objects described by a set of data. people, animals, or things. What we collect information
on.
15. Variables: are the characteristics or measurements that we are interested in studying. Specific aspects of the
individuals that we collect data on. Can be either quantitative (numerical) or categorical (qualitative-Fav color, gender,
job).
16. Data: are the actual values of the variables
17. The ____ is the 100 first-year students who were randomly surveyed.
The ____ is a group of students who graduated from the university last year,
randomly selected: Sample
18. The ____ is all first-year students attending Strime University this term.
The ____ is a group of all students who graduated from the university last
year.: Population
19. The ____ is the average (mean) amount of money spent (excluding books) by
first-year university students in the sample.
The ____ is the average cumulative GPA of students in the study who graduated
from the university last year.: Statistic
, Data Literacy D772 WGU
Study online at https://quizlet.com/_hq99qs
20. The ____ could be the amount of money spent (excluding books) by one
first-year student.
The ____ is the cumulative GPA of one student who graduated from the univer-
sity last year.: Variable
21. The ____ are the dollar amounts spent by the first-year students.
The ____ consists of the values 3.65, 2.80, 1.50, 3.90.: Data
22. The ____ is the average (mean) amount of money spent (excluding books) by
first-year university students at Strime University this term.
The ____ is the average cumulative GPA of students who graduated from the
university last year.: Parameter
23. Strata: Subgroups within a population that share a common characteristic (e.g., age group, gender, income
level).
24. Strata (Example): A high school population might be divided into strata based on grade level (freshmen,
sophomores, juniors, seniors).
25. Proportionate Sample: A sample where the number of individuals selected from each stratum is
proportional to the size of that stratum in the population.
26. Proportionate Sample (Example): If 25% of the high school population is freshmen, then 25% of
the sample should also be freshmen.
27. Stratified sampling: involves dividing the population into distinct subgroups called strata, based on
specific characteristics such as age, gender, or socioeconomic status. Once the population is divided into strata, a
random sample is taken from each stratum in proportion to its representation in the overall population. This ensures
that the sample reflects the diversity of the population in terms of the chosen characteristics
28. Cluster sampling: involves dividing the population into clusters, which are naturally occurring groups like
schools, neighborhoods, or cities. Instead of randomly selecting individuals from the entire population, researchers
randomly select a few clusters and include all individuals within those selected clusters in the sample. This method is
often used when it's difficult or expensive to sample individuals directly from the entire population
29. Cluster: A naturally occurring group within a population (e.g., school, neighborhood, city).
30. Cluster (Example): A researcher studying the opinions of high school students in a state might randomly
select five schools and survey all students within those schools.
31. Systematic sampling: involves selecting every "nth" individual from a list of the population, starting from
a randomly chosen point. This method is often used when it's easy to access a list of the entire population. It's a simple
and efficient method
