Key Ingredients to Inferential Statistics

Question 1

number of standard deviations that a score is above (or below, if it is negative) the mean of its distribution; it is an ordinary score transformed so that it better describes the score’s location in a distribution

Answer 1

z-score

Question 2

also called the Gaussian distribution

Answer 2

Normal Distribution

Question 3

the extent to which an event is likely to occur as determined by the the fraction or proportion of successful outcomes to all the possible outcomes

Answer 3

probability

Question 4

term used in discussing probability for the result of an experiment (or almost any event)

Answer 4

outcome

Question 5

requires that each individual in the population has an equal chance of being selected

Answer 5

random sampling

Question 6

keeping the probabilities from changing from one selection to the next by returning each individual to the population before you make a selection

Answer 6

sampling with replacement

Question 7

specific list of the members of the population in order to select a subset of that population

Answer 7

sampling frame

Question 8

basic unit that represents whatever is being sampled and from which survey data are to be gathered

Answer 8

element

Question 9

uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample.

Answer 9

probability sampling

Question 10

participants has an equal chance of getting selected to be the part sample

Answer 10

simple random sampling

Question 11

divides the elements of the population into small subgroups (strata) based on the similarity in such a way that the elements within the group are homogeneous and heterogeneous among the other subgroups formed

Answer 11

stratified random sampling

Question 12

entire population is divided into clusters or sections and then the clusters are randomly selected. All the elements of the cluster are used for sampling.

Answer 12

cluster sampling

Question 13

entire cluster is selected randomly for sampling.

Answer 13

single stage

Question 14

first, we randomly select clusters and then from those selected clusters we randomly select elements for sampling

Answer 14

two stage

Question 15

a probability sampling method where the elements are chosen from a target population by selecting a random starting point and selecting other members after a fixed ‘sampling interval’.

Answer 15

systematic sampling

Question 16

it is the combination of one or more methods described above

Answer 16

multistage sampling

Question 17

a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.

Answer 17

non-probability sampling

Question 18

the samples are selected based on the availability

Answer 18

convenience sampling

Question 19

sampling technique that is based on the intention or the purpose of study.

Answer 19

purposive sampling

Question 20

sampling technique wherein the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon.

Answer 20

quota sampling

Question 21

this technique is used in the situations where the population is completely unknown and rare

Answer 21

referral/snowball sampling