week 1 - measurement

Question 1

define population and give example

Answer 1

the entire set of individuals, or events, of interest in a particular study.
- all Australian workers

Question 2

define sample and give an example

Answer 2

set of individuals selected from a population

- 100 Australian workers from each state

Question 3

what is the difference between population and sample

Answer 3

• population is not feasible

- sample is a small set of the population

Question 4

define parameter and give an example

Answer 4

a value that describes a key characteristic of the population
- average income of all Australians

Question 5

how could you get the parameter of the population?

Answer 5

from census data

Question 6

define statistic and give an example

Answer 6

a value that describes a key characteristic of the sample, and are used to generalise for all population
- average IQ of a sample of 100 Australian Uni students

Question 7

what is the difference between parameter and statistic?

Answer 7

• the parameter refers to characteristics of the POPULATION whereas a statistic refers to a characteristic of the SAMPLE within the population
• the statistic generalises for all the population, whereas the parameter is data straight from the population

Question 8

explain how we use data to answer our research questions

Answer 8

through the use of statistics, we use mathematics to organise, summarise and interpret numerical data.

Question 9

what are the two main types of statistics?

Answer 9

• descriptive statistics

- inferential statistics

Question 10

explain descriptive statistics

Answer 10

simply used to describe and summarise data

• includes averages (mean, median, mode), score ranges etc.
• makes data manageable by simplifying it

Question 11

explain inferential statistics

Answer 11

used when we want to answer research questions

- allows us to make generalisations from our sample to our population of inerest

Question 12

define a variable

Answer 12

a characteristic or condition that changes or has different values for different individuals
- e.g. depression, age

Question 13

what are the two main types of variables?

Answer 13

• discrete

- continuous

Question 14

explain discrete variables and give an example

Answer 14

• often referred to as categorical data
• contain only a small number of values
• is discrete because it only has a small number of possible categories
• e.g. handedness (right/ left/ ambi)

Question 15

explain continuous variables

Answer 15

• often referred to as measurement data
• contain many different values/ categories
• e.g. weight (40kg-140kg)

Question 16

what are the determinants of whether a variable is discrete or continuous

Answer 16

the way you set up the measurement.
- e.g. anxiety may be considered continuous, however if you categorise anxiety into groups (high vs low anxiety) then it is a discrete variable.

Question 17

how are continuous data normally summarised

Answer 17

using average (means)
- e.g. mean age of AFL footballers is 188cm

Question 18

how are discrete data summarized numerically?