Chapter 1

Question 1

What is Descriptive Statistics?

Answer 1

Collecting and organizing data such as numerical summaries, tables, and graphs.

For example, the average test score in a science class.

Question 2

What is Inferential Statistics?

Answer 2

Analyzing and interpreting data, using sample data to make a statement about what we believe to be true in the population, with a certain measure of reliability.

For example, collecting data based on test scores and relating it to time students study, concluding that studying longer increases test scores.

Question 3

What is an Individual in statistics?

Answer 3

A person or object that you are interested in finding out information about.

Example: If determining the amount of tattoos HCC students have, the individual would be an HCC student.

Question 4

What is a Variable?

Answer 4

The measurement or observation of the individual.

Example: The variable is what is being measured, such as the response to a question.

Question 5

What is a Population?

Answer 5

The set of all values of the variable for the entire group of individuals.

Example: When questioning HCC students about their number of tattoos, the population is ALL HCC students.

Question 6

What is a Sample?

Answer 6

The subset from the population.

Example: When questioning HCC students about their number of tattoos, the sample is the amount polled, such as the subset of 100 students.

Question 7

What is a Parameter?

Answer 7

Number calculated from the population, fixed.

Examples: p, μ, σ; percentage of ALL students having a tattoo.

Question 8

What is a Statistic?

Answer 8

Number calculated from the sample, readily known, and used to estimate the parameter value.

Examples: 𝑝̂, 𝑥̄, s; percentage of sample size (~100 students) having a tattoo.

Question 9

What is Quantitative data?

Answer 9

Numerical value, data is in numbers that can be counted or measured.

Example: Household income, number of pets.

Question 10

What is Qualitative data?

Answer 10

Data that is written in words, describes a quality of the individual.

Example: Ethnicity, hair color, gender.

Question 11

What is Discrete Quantitative Data?

Answer 11

Data can only take on particular values, like integers, can be counted.

Example: Number of pets.

Question 12

What is Continuous Quantitative Data?

Answer 12

Data can take on any value, usually measured.

Example: Household income.

Question 13

What is Nominal Data?

Answer 13

Data that consists of names or categories, such as gender, car names, ethnicity, and race.

Question 14

What is Ordinal Data?

Answer 14

Data is nominal but also can be put into order since one value is more or less than another value.

Example: Test grades, placement in a competition, and drink sizes.

Question 15

What is Interval Data?

Answer 15

Data is ordinal but also can be subtracted or added from one another.

Example: Temperature and time.

Question 16

What is Ratio Data?

Answer 16

Data is interval but can also be multiplied or divided from another.

Example: Height or weight (The man is two TIMES taller than his son).

Question 17

What is a Census?

Answer 17

When every individual of interest is measured.

Question 18

What is Simple Random Sampling?

Answer 18

A sample that is selected from a population in a way that ensures that every different possible sample has the same chance of being selected.

Example: Writing everyone’s name in a hat and blindly selecting someone.

Question 19

What is Stratified Sampling?

Answer 19

Breaking a population into groups called strata, then taking a simple random sample from each strata.

Example: Separating a group of people based on their ethnicity, then blindly selecting individuals from each ethnic group.

Question 20

What is Cluster Sampling?

Answer 20

Breaking the population into clusters, randomly choosing a cluster and polling every individual within it.

Example: Randomly creating groups based on no similarities, then selecting a random group and polling everyone from said group.

Question 21

What is Systematic Sampling?

Answer 21

Randomly choose a starting point, then select every kth individual to measure.

Example: Picking a random number (such as the 4th person) and then proceeding to poll every 10th individual following the 4th person.

Question 22

What is Convenience Sampling?

Answer 22

Choosing individuals based on how easy they would be to poll (unreliable).

Example: Only polling your friends, who are more likely to share the same views as you.

Question 23

What is an Observational Study?

Answer 23

When an investigator collects data merely by watching or asking questions but does not change anything.

Example: Polls.

Question 24

What is an Experiment?

Answer 24

When an investigator changes a variable or imposes a treatment to determine its effect.

Example: Trying out a new medicine.

Question 25

What is a Blind Study?

Answer 25

Where an individual is not aware if they are receiving a treatment or a placebo, but the researcher does know.

Question 26

What is a Double-Blind Study?

Answer 26

Where neither the researcher nor the individual are aware if they are receiving a treatment or placebo.

Question 27

What can designed experiments establish?

Answer 27

Causation.

Question 28

What can observational experiments establish?

Answer 28

Association.

Question 29

What is Sampling Error?

Answer 29

An error that results because there is a difference between the sample results and the true population results.

Question 30

What is Non-Sampling Error?

Answer 30

An error that results during data collection, causing the data to differ from the true values. ## Footnote Example: Mistyping information/integers.

Question 31

What is Selection Bias?

Answer 31

Results when part of the population is excluded so that those experimental units have little to no chance of being selected in the sample.

Question 32

What is Nonresponse Bias?

Answer 32

Results when the researchers conducting a survey or study are unable to obtain data on all experimental units selected for the example. ## Footnote Example: Having a survey that needs to be answered via the phone or mail.

Question 33

What is Measurement Error?

Answer 33

Inaccuracies in the values of the data recorded. ## Footnote Example: Online surveys that do not entail the answer you are looking for.

Question 34

What is Overgeneralization?

Answer 34

Where you do a study on one group and then attach that data to assume it will happen on all groups.

Question 35

What is a Lurking Variable?

Answer 35

Causes change in both the explanatory and response variable in the study. ## Footnote Example: Determining that the number of firefighters involved increases the amount of damage, yet the lurking variable is the seriousness of the fire.

Question 36

What is a Confounding Variable?

Answer 36

Causes a change in the response variable during the study. ## Footnote Example: Determining if drinking carrot juice proves a healthy heart, but the real cause to a healthy heart is a healthy lifestyle.