2.5 Measure of Location and Outliers

Question 1

Measure of Location

Answer 1

tells us about an observation relative standing in the distribution, common measures are percentiles and quartiles

Question 2

Percentiles

Answer 2

a measure of location that divides the data into 100 groups with roughly 1% of the values in each group

Question 3

How to find the persentile

Answer 3

number of values less than x divided by the total number of values then multiply by 100

Question 4

Finding the kth percentile

Answer 4

sort data, use location function L=(k/100)*n where k=percentile and n=total number, if L is a whole number count in your data set to L, if L is not a whole number, round up then count to find your value

Question 5

Quartiles

Answer 5

special cases of percentiles, Q1=25th, Q2=50th (median), Q3=75th

Question 6

Median

Answer 6

halfway point, if n is odd then its the middle ordered data value, if n is even then its the average of the two middle ordered data values

Question 7

Location Function to find the mediam

Answer 7

L(M)= n+1/2

Question 8

How to find Q1

Answer 8

look at the lower half of the data, to the left of the median and find the median for the lower half

Question 9

How to find Q3

Answer 9

look at the upper half of the data values, to the right of the median, and find the median of the upper half

Question 10

IQR

Answer 10

Q3-Q1, only takes into account 50% of the data

Question 11

Fence Rule

Answer 11

Checking for outliers using quartiles, value less than the lower fence or greater than the upper fence could be considered an outlier

Question 12

Lower Fence

Answer 12

Q1-(1.5*IQR)

Question 13

Upper fence

Answer 13

Q3+(1.5*IQR)

Question 14

Causes of outliers

Answer 14

measurement errors, data entry error, sampling error, chance occurrence