Lecture 3

Question 1

descriptive statistics focus on…

Answer 1

summarising & presenting data

Question 2

tables & data visualisation portray…

Answer 2

data

Question 3

2 types of descriptive statistics?

Answer 3

measures of central tendency
measures of variability

Question 4

measures of central tendency?

Answer 4

median, mean, mode

focuses on the average or middle values

Question 5

measures of variability?

Answer 5

standard deviation, range, variance, quartiles

focuses on the dispersion of data

Question 6

how to calculate standard deviation?

Answer 6

Step 1: Find the mean.
Step 2: Subtract the mean from each score.
Step 3: Square each deviation.
Step 4: Add the squared deviations.
Step 5: Divide the sum by the number of scores.
Step 6: Take the square root of the result from Step 5.

Question 7

how to calculate variance?

Answer 7

Calculate the mean of the data.

Find each data point’s difference from the mean value.

Square each of these values.

Add up all of the squared values.

Divide this sum of squares by n – 1 (for a sample) or N (for the population).

Question 8

variables = ?

Answer 8

factors that can take on more than one value

can vary in value

Question 9

distribution = ?

Answer 9

refers to the different values that can be assumed and their frequency

how often each value occur

Question 10

for discrete data, we care especially about….

Answer 10

commonly occurring values (mode)
unusual values (e.g., outliers)

Question 11

discrete data = ?

Answer 11

data that is counted, not measured

(e.g., the number of dogs, population)

Question 12

continuous data = ?

Answer 12

can take on any value in an interval

(e.g., 1<x<10, can be 1.3, 5.6, 7.2 etc)

Question 13

univariate descriptive statistics = ?

Answer 13

describing one variable at a time

Question 14

the benefits of good graphics?

Answer 14

presents ideas with clarity, efficiency and precision

Question 15

exhaustive = ?

Answer 15

fully comprehensive

considers all elements of interest in a dataset

Question 16

what do statistics involve?

Answer 16

the collection, description, analysis and inference of conclusions based on data

Question 17

categorical data = ?

Answer 17

data that reflects qualitative characteristics

AKA Qualitative data

assigns numbers values to qualitative data (e.g., 1=female, 2=male)

Question 18

numerical data = ?

Answer 18

data that are naturally numbers based

e.g., age, height, weight

Question 19

what levels of measurement come under categorical data?

Answer 19

nominal & ordinal

Question 20

what levels of measurement come under numerical data?

Answer 20

interval & ratio

Question 21

nominal level data?

Answer 21

describes qualitative characteristics or groups

no inherent numerical order/rank

e.g., gender, ethnicity, colours

often used in surveys

Question 22

ordinal level data?

Answer 22

the same as nominal data as it describes categories

but ordinal level data can be ranked in order

e.g., level of income, level of satisfaction, level of agreement

Question 23

interval level data?

Answer 23

numerical data that involves quantitative data

has an order and equal spaces between points

e.g., range of test score 0-30 = C, 30-60 = B, 60-100 = A

arbitrary 0 point

Question 24

ratio level data?

Answer 24

ordered/ranked quantitative data

equal distance between points

e.g., length of time, weight, height, length

non-arbitrary zero point

Question 25

arbitrary zero point?

Answer 25

zero doesn’t mean it doesn’t exist

e.g., 0 degrees isn’t an absolute be-all-end-all, as degrees can be -1

height, however, cannot be below zero

Question 26

frequency = ?

Answer 26

the number of times something occurs

Question 27

what are the distributional features of interest on a frequency table?

Answer 27

unusual and commonly occurring features of interest

patterns

Question 28

must variable names be meaningful?

Answer 28

yes

Question 29

good practice with tables?

Answer 29

• avoid vertical lines
• minimal horizontal lines to avoid confusion
• separate table contents from title & notes
• separate headings from the rest of the data

Question 30

pie charts are good at presenting data when…

Answer 30

• discrete variable
• exhaustive
• small number of categories
• real variation across categories

Question 31

benefits of bar charts?

Answer 31

enables direct comparison

Question 32

purpose of graphs & tables?

Answer 32

powerful way of communicating complex information clearly & accurately