intro to statistics and data

Question 1

population

Answer 1

defined collection of units interested in studying

Question 2

branches of statistics and probability

Answer 2

• descriptive statistics
• probability statistics
• inferential statistics

Question 3

descriptive statistics

Answer 3

• describes data
  ex) sample of 2500

15% of dog owners in our sample walk their twice a day

Question 4

probability statistics

Answer 4

methods to use known properties of a population to draw a conclusion about a sample

Question 5

inferential statistics

Answer 5

• make predictions or generalizations
• > estimate parameters
• > hypothesis tests
  ex) sample of 2500

300,000 people walk their dog twice a day

Question 6

Statistical Process

Answer 6

• collection
• organization
• presentation
• analysis

Question 7

census

Answer 7

when desired info is gathered for all units in the population

Question 8

sample

Answer 8

subset of units from which we collect data

Question 9

variable

Answer 9

any characteristic that can be different values for each unit in a population

Question 10

categorical (qualitative) variable

Answer 10

places an individual into one of several groups or categories (ex, gender or race)

Question 11

nominal

Answer 11

-> named variables

Nominal data is a categorical (qualitative) data type, so it describes qualitative characteristics or groups, with no order or rank between categories

(qualitative data)

examples)

Gender, ethnicity, eye colour, blood type

Brand of refrigerator/motor vehicle/television owned

Political candidate/party preference, shampoo preference, favourite meal

Question 12

ordinal

Answer 12

-> named + ordered variables

Ordinal data is the same as nominal data in that it’s looking at categories, but unlike nominal data, there is also a meaningful order or rank between the options.

An ordinal scale is one where the order matters but not the difference between values

(qualitative data)

examples)

Socio economic level (e.g. low income, middle income, high income)

Income level (“less than 50K”, “50K-100K”, “over 100K”)

Political orientation (e.g. far left, left, centre, right, far right)

Level of agreement (e.g. strongly disagree, disagree, neutral, agree, strongly agree)

Question 13

quantitative (numerical) variable

Answer 13

is a characteristic that can be counted (ex, number of people in house) or measured (ex, height or weight)

quantitative data can be an interval or ratio

Question 14

interval

Answer 14

-> named + ordered + proportionate interval between variables (ex, temperature, celcius, ferinheit) (difference, subtracting) (no true 0 starting point)

(quantitative data)

Question 15

ratio

Answer 15

-> named + ordered + proportionate interval between variables + has a true “0 starting point” (ex, height) (fractions, dividing) (temperature, kevlins)

(quantitative data)

Question 16

discrete data

Answer 16

it can only have specific values

“counted”

ex) number of people in class, questions answered correctly, shoe size, 1, 2, 3, 4, 5

Question 17

continuous data

Answer 17

it can take on any value in an interval

“measured”

ex) weight, length, 1, 1.3, 2.46, 5.389