stats

Question 1

variable

Answer 1

A variable is a characteristic or attribute that can assume different values.

Question 2

random variables

Answer 2

A variable whose values are determined by chance are called random variables.

Question 3

population

Answer 3

A population consists of all subjects (human or otherwise) that are being studied.

Question 4

Descriptive statistics

Answer 4

Descriptive statistics consists of the collection, organization, summarization, and presentation of data.

Question 6

Inferential statistics

Answer 6

Inferential statistics consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions.

Question 7

Hypothesis testing

Answer 7

Hypothesis testing is a process for evaluating claims about a population, based on information obtained from a sample.

Question 8

qualitative variable

Answer 8

A qualitative variable is a variable that has distinct categories according to some characteristic or attribute.

Question 9

quantitative variable

Answer 9

A quantitative variable is a variable that can be counted or measured.

Question 10

discrete variable

Answer 10

A discrete variable assumes values that can be counted, or assigned values such as 1, 2, 3 and so on.

Question 11

continuous variable

Answer 11

A continuous variable assumes values within an interval, and can have infinitely many values between any two specific values. They are obtained by measuring. They often include fractions or decimals.

Question 12

boundary

Answer 12

The boundary of a number is the class of values in which the data value would fall before being rounded.

Question 13

There are four common measurement scales used to classify variables.

Answer 13

Qualitative variables can have the nominal level of measurement or the ordinal level of measurement.

Quantitative variables can have the interval level of measurement or the ratio level of measurement.

Question 14

nominal level of measurement

Answer 14

The nominal level of measurement classifies data into mutually exclusive (non-overlapping) categories in which there is no natural order or ranking of the categories.

Question 15

ordinal level of measurement

Answer 15

The ordinal level of measurement classifies data into categories that can be ranked; however, precise differences between the ranks do not exist.

Question 16

random sample

Answer 16

A random sample is a sample in which all members of the population have an equal chance of being selected.

Question 17

systematic sample

Answer 17

A systematic sample is a sample obtained by selecting every kth member of the population, where k is a counting number.

Question 18

cluster sample

Answer 18

A cluster sample is obtained by dividing the population into sections or clusters and then selecting one or more clusters at random, and using every member of the selected cluster or clusters as the sample.

Question 19

stratified sample

Answer 19

A stratified sample is a sample obtained by dividing the population into subgroups or strata according to some characteristic relevant to the study. Then subjects are selected at random from each subgroup.

Question 20

convenience sample

Answer 20

A convenience sample is a sample chosen out of convenience, with no randomization. For example, a restaurant manager asks everyone at the restaurant one evening to rate the service on a scale from 1 to 5.

Question 21

treatment group

Answer 21

The treatment group of an experimental study is the group that receives the new drug or treatment that the study is evaluating.