Chapter 1 - Statistics, Data, and Statistical Thinking

Question 1

Statistics

Answer 1

The science of data.
It involves collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical and categorical information.

Question 2

[1.2] Descriptive Statistics

Answer 2

Utilizes NUMERICAL and graphical methods to explore data, i.e, to look for patterns in a data set, to summarize the info. revealed in a data set, and to present the info. in a convenient form.

Question 3

Inferential Statistics

Answer 3

Utilizes sample data to make…

ESTIMATES, DECISIONS, PREDICTIONS, OR OTHER GENERALIZATIONS about a larger set of data.

Question 4

[1.3] Experimental (or observational) unit

Answer 4

Is an object

example: person, thing, transaction, or event) upon which we collect data

Question 5

Population

Answer 5

A set of units (usually people, objects, transactions, or events) that we are interested in studying.

Question 6

Variable

Answer 6

A characteristic or property of an individual experimental (or observational) unit.

Question 7

Measurement

Answer 7

The process we use to assign numbers to variables of individual population units.

Example: Measuring the preference for a food product by asking a consumer to rate the product’s taste on a scale from 1-10.

Question 8

Census

Answer 8

When we measure a variable for every experimental unit of a population. “EVERYONE”.

Example: You’re doing a survey travel time by asking students at school.
> Asking everyone at school is a CENSUS of the school.
> But asking only 50 students is a SAMPLE of the school.

Question 9

Sample

Answer 9

A subset of the units of a population.

Question 10

Statistical inference

Answer 10

An estimate or prediction or some other generalization about a population based on information contained in a sample.

Example: The sample of 100 invoices, the auditor may estimate the total number of invoices containing errors in the population of 15,000 invoices. [Figure 1.2]

Question 11

Reliability

Answer 11

How good the inference is.
- The only way we can be certain that an inference about a population is correct is to include the entire population (census?) in our sample.

Question 12

Measure of reliability

Answer 12

A statement (usually quantified) about the degree of uncertainty associated with a statistical inference.

Question 13

Four Elements of DESCRIPTIVE Statistical Problems

Answer 13

1. The POPULATION or SAMPLE of interest
2. one or more variables (characteristics of the population or experimental units that are to be investigated)
3. Tables, graphs, or numerical summary tools
4. Identification of patterns in data

Question 14

Five Elements of INFERENTIAL Statistical Problems

Answer 14

1. The population of interest
2. One or more variables (characteristics of the population or experimental units) that are to be investigated
3. The sample of population units
4. The inference about the population based on information contained in the sample
5. A measure of reliability for the inference.

Question 15

[1.4] Process

Answer 15

A series of actions or operations that transforms inputs to outputs.
- A process produces or generates output over time.
Example: Processes of interest to businesses are those of production or manufacturing.

Question 16

Black box

Answer 16

A process whose operations or actions are unknown or unspecified.

Question 17

Sample

Answer 17

Any set of output (object or numbers) produced by a process is also called a sample.

Question 18

Quantitative data

Answer 18

Measurements that are recorded on a naturally occurring numerical scale.

Example: The temperature (in degrees Celsius) at which each unit in a sample of 20 pieces of heat-resistant plastic begins to melt.

• Unemployment rare (%)
• Score of a sample on the GMAT or MCAT
• Number of females employed in each of a sample of 75 manufacturing companies

Question 19

Qualitative Data (categorical)

Answer 19

Measurements that CANNOT be measured on a natural numerical scale; only classified into one of a group of categories.

Example:

• Political party affiliation
• Defective status (defective or indefective)
• Size of a car (subcompact, mid-size, full-size)
• A taste tester’s ranking (best, worst, etc.)

Question 20

Three ways of obtaining data

Answer 20

1. Published source
2. Designed experiment
3. Observational study (e.g., a survey)

Question 21

[1.6] Published source

Answer 21

A book, journal, newspaper, or Web site.

Question 22

Designed experiment

Answer 22

Researcher exerts full-control over the characteristics of the experimental units sampled.

Example: A group of experimental units that are assigned the treatment and an untreated (or control) group.

Question 23

Observational study

Answer 23

Experimental units are OBSERVED in a natural setting. No attempt is made to control the experimental units sampled.

Example: Opinion polls, surveys.

Question 24

What’s so significant about surveys?

Answer 24

Most common type of observational study, where the researcher samples a group of people to ask questions and record responses.

Question 25

Representative sample

Answer 25

Exhibits characteristics typical of those possessed by the population of interest.

Question 26

Simple random sample (?)

Answer 26

Ensures that every subset of fixed size in the population has the same chance of being included in the sample.

Question 27

Random number generator

Answer 27

[Self explanatory]
Typical procedure for selecting a simple random sample. Generators are available in table form, online, and other statistical software packages.

Example: Excel/XLSTAT, Minitab, andSPSS

Question 28

Selection bias

Answer 28

Results when a subset of experimental units in the population has little or no chance of being selected for the sample.

Question 29

Nonresponse bias

Answer 29

A type of selection bias that results when the response data differ from the potential data for the nonresponders responders.

Question 30

Measurement error

Answer 30

Refers to inaccuracies in the values of the data collected.

Example: In surveys, the error may be due to ambiguous or leading questions and the interviewer’s effect on the respondent.

Question 31

[1.7] Business analytics

Answer 31

Refers to methodologies (e.g statistical methods) that extract useful information from data in order to make better business decisions.

Question 32

Statistical thinking

Answer 32

Involves applying rational thought and the science of statistics to critically assess data and inferences.

Question 33

Unethical statistical practice

Answer 33

When the selection bias in the sample was intentional with the sole purpose to mislead the public.