lecture 5

Question 1

what are guidelines for chosing K

Answer 1

K = [10/3 log10 (n)] +1
log10 = log base ten
n = total number obs
k often rounded to integer
gives indication of just the right number

Question 2

what makes a histogram easier to read

Answer 2

when bin ends fall on interval points on x axis
use more interpretable intervals
can choose scale that best fits *consider range of data

Question 3

how does density change histogram

Answer 3

vertical scale changes
multiply by bin width (interval width)

Question 4

what does histogram show

Answer 4

need labels - shows spread, min/max
just see categories of data not whole SET

Question 5

WHAT CAN we deduce from histogram

Answer 5

the number (or the propor- tion) of observations in a given interval
can add up heights of rectangles within interval
tricky if only part of rectangle if included

Question 6

what do we lose with histograms

Answer 6

know nothing about distribution of observations within rectangle itself
Access to fine data bc only seeing a frequency summary

Question 7

what happens when All of the observations in the rectangle are included in the interval - histograms

Answer 7

add entire rectangle height

Question 8

what happens when None of the observations in the rectangle are included in
the interval - histograms

Answer 8

do not add rectangle at all

Question 9

what happens when fraction of obs in rectangle included in interval - histograms

Answer 9

add same fraction of rectangle height
(half a bin)
can only make approximation

Question 10

what are numerical measures of central tendency

Answer 10

try to capture where data situated
where on x axis its located
descriptive statistics

Question 11

name measures of central tendency

Answer 11

mean/average
median
mode

Question 12

what is sample mean

Answer 12

sample average
add all up and divide by total
number of obs

ex = 3,5,5,6,8
(3+5+5+6+8)/5 = 5.4

Question 13

what happens to sample mean when have a super large value in a set of small value numbers

Answer 13

mean pulled away from smaller values towards larger

Question 14

what happens to sample mean when have a super small value in a set of large value numbers

Answer 14

mean pulled away from larger values towards smaller ones

Question 15

what are outliers

Answer 15

extreme obs in sample

Question 16

what do outliers do

Answer 16

distort sample mean as a measure of central tendency
must be careful when outliers present

Question 17

is sample mean a good measure of central tendency

Answer 17

maybe not in presence of outliers

Question 18

what is sample median

Answer 18

m
number if we ordered number from smallest to largest then it would be the middle
50% data points in sample below median and 50% above median

Question 19

is median always super simple

Answer 19

nooo
if odd = has middle
but if even = more complicated
if has ties in data = multiple identical numerical values = all numbers in middle the same
have specific rules for special cases

Question 20

what happens if n odd - median

Answer 20

m = (n+1)/2 position

Question 21

what happens if n even - median

Answer 21

m = average of (n/2)th and (n/2 +1)th position

Question 22

is sample median heavily influenced by outliers

Answer 22

NOOO
median probably wont change due to outliers
median is robust to outlying observations