histograms and quartiles

Question 1

quantitative variables

Answer 1

numerical values

Question 2

categorical variables

Answer 2

names that aren’t necessarily logically ordered

- can be coded; female = 1

Question 3

ordinal variables

Answer 3

categorical variables that have logical ordering such as N, P, C, D, HD
- can’t compute or average

Question 4

distributions

Answer 4

two sets of numbers: values variables take and frequency

histogram displayed frequency distribution (no gaps)

Question 5

features of a histogram

Answer 5

location: where is the centre - mean, median, mode
spread: what is the variability - deviation, gaps, outliers
shape; what is the distribution? - unimodal (one peak), multimodal, symmetric, skewed

Question 6

median

Answer 6

the midpoint (50th percentile or Q2)

Question 7

first quartile

Answer 7

25% below, 75% above. 25th percentile

Question 8

third quartile

Answer 8

Q3 has 75% below

Question 9

quantiles

Answer 9

a value that is greater than a given proportion of data. 0.1 is above 10%

Question 10

cumulative distributions

Answer 10

counts are added up
should add to one
what proportion of the data is less than 10?

Question 11

a rule for quartiles

Answer 11

• calculate 0.25n where n is the number of values
• if it is an integer, count off that many values in the ordered list, Q1 is halfway between that value and the next
• if its not an integer, round up and do the same
• for Q3, do the same but from the top
• can be done for any quantile

Question 12

measuring spread

Answer 12

interquartile range: IQR = Q3-Q1 and gives the middle 50% of the data

range: max-min (not as useful as IQR)

Question 13

randomising variables in excel

Answer 13

type out values/names in column B

• =RAND(), return in column A
• drag =RAND down to fill column A
• select column A and B and sort ascending