Lecture 1

Question 1

What are descriptive statistics?

Answer 1

Measures of central tendency and measures of dispersion. Simply describes the data

Question 2

Measures of central tendency

Answer 2

Mean, Median and Mode

Question 3

Measures of dispersion

Answer 3

Range, Standard deviation, Variance and Absolute Deviation

Question 4

What are inferential statistics?

Answer 4

Hypothesis Testing and Regression Analysis. Used to see if trends in sample data are a true representation of trends in the population

Question 5

Hypothesis Testing

Answer 5

Z-Test, T-Test and F-Test

Question 6

Regression Analysis

Answer 6

Linear Regression

Question 7

Population

Answer 7

All the individual items that could be studied.

Question 8

Sample

Answer 8

A selection of items from the population

Question 9

Data collected from subjects is called…

Answer 9

Observations

Question 10

Individual items in a sample

Answer 10

Subjects/ Sample Units/ Cases

Question 11

Differences between subjects are….

Answer 11

Variables (maybe fields)

Question 12

Data

Answer 12

Numerical information that we use to extract and interpret meaning

Question 13

Quantitative Data

Answer 13

Information has a directly measurable (numerical) value. E.g. height, weight, age

Question 14

Qualitative Data

Answer 14

Information that is non-numerical and most often descriptive. E.g. good or bad. Often categorical

Question 15

Categorical Data

Answer 15

Data fits into named categories with no in-between. E.g. Blood type. Includes nominal data and ordinal data

Question 16

Nominal Data

Answer 16

No ordering to the categories. E.g. Alive vs Dead, Political Affiliation, Species of Snail. Discrete

Question 17

Ordinal Data

Answer 17

Has an ordering to the data. E.g. sporting scores and fixture. IMPORTANT: these orderings are not mathematically linked. E.g. the winners of the world cup are not twice as much the “winners” as the runners up. Used for comparisons

Question 18

Quantitative Data Types

Answer 18

Discrete Data and Continuous Data

Question 19

Discrete Data

Answer 19

Can only take certain values. E.g. when counting the number of people, we cannot have half a person

Question 20

Continuous Data

Answer 20

Can take any value within a given range. E.g. height, weight, blood pressure

Question 21

Continuous Data Types

Answer 21

Interval and Ratio

Question 22

Interval

Answer 22

Can take any value within a given range, but a value of zero does not indicate an absolute zero

Question 23

Ratio

Answer 23

Can take any variable within a range. The value doesn’t need to be a whole number but the zero must be a true zero. E.g. height of a house. Continuous

Question 24

Is Temperature an Interval or Ratio Variable?

Answer 24

Interval - 0ºC is not true zero. Note: 100ºC is not twice the temperature of 50ºC

Question 25

Levels of Measurement

Answer 25

Nominal, Ordinal, Interval and Ratio

Question 26

Can Qualitative Data be converted to Quantitative Data for Analysis?

Answer 26

Yes. E.g. Pain scale, happiness meter