Chapter 1

Question 1

Statistics definition

Answer 1

The science of collecting, analyzing, presenting, and interpreting data, and making decisions based on these analyses.

Question 2

2 main types of statistics

Answer 2

1. Descriptive
2. Inferential

Question 3

Descriptive statistics

Answer 3

Consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures.
Ex: deaths due to red-light running

Question 4

Inferential statistics

Answer 4

Consists of methods that use sample results to help make decisions or predictions about a population.
Ex: is anxiety and depression a major problem among teens.

Question 5

Variable definition

Answer 5

A characteristic under study that assumes different values for different elements.

Question 6

Observation or measurement

Answer 6

The value of a variable for an element.

Question 7

Types of variables

Answer 7

1. Qualitative
2. Quantitative

Question 8

Types of quantitative variables

Answer 8

1. Discrete
2. Continuous

Question 9

Qualitative (or categorical) variable

Answer 9

A variable that cannot assume a numerical value but can be classified into 2 or more nonnumeric categories.
Ex: colour, birthplace, blood type

Question 10

Quantitative variable

Answer 10

A variable that can be measured numerically.
Ex: child number, height, cars owned

Question 11

Discrete quantitative variable

Answer 11

Values are countable.
Ex: number of cars, population

Question 12

Continuous quantitative variable

Answer 12

Can assume any value over a certain interval or intervals.
Ex: weight, length

Question 13

Cross-section data

Answer 13

Data collected on different elements at the same point in time or for the same period of time.

Question 14

Time-series data

Answer 14

Data collected on the same element for the same variable at different points in time or for different periods of time.

Question 15

Population

Answer 15

Consists of all elements whose being studied.

Question 16

Sample

Answer 16

A portion of the population selected for study.

Question 17

Why would you use sample over population data?

Answer 17

1. Using whole population data is not always feasible.
2. We can used sample to make inferences or draw conclusions about a population.

Question 18

Sampling error

Answer 18

The difference between the result obtained from a sample survey and the result that would have been obtained from the whole population.
Cannot be avoided.

Question 19

Non-sampling error or biases

Answer 19

Errors that occur in the collection, recording, and tabulation of data.
Can be minimized if questions are prepared carefully and data is handled cautiously.

Question 20

4 non-sampling errors types

Answer 20

1. Selection error
2. Non response error
3. Response error
4. Voluntary response error

Question 21

Simple random sample

Answer 21

Every member has an equal probability of being selected.

Question 22

Systematic random sampling

Answer 22

We select every kth person.

Question 23

Stratified random sample

Answer 23

1. Divide the population into subgroups, based on some characteristic.
2. A random sample is selected from each group. The number of samples in each group is proportional to-he groups population size.

Question 24

Cluster sampling

Answer 24

1. Divide the whole population into groups called clusters.
2. Each cluster is representative of the population.
3. A random sample of clusters is selected.