Central Tendency, Dispersion, and Visualizing Data

Question 1

three measures of central tendency

Answer 1

mean, median, mode

Question 2

mode

Answer 2

most frequent occurring in the data

Question 3

pros of mode

Answer 3

• best if data is nominal
• if rough estimate needed
• its a number in your data set

Question 4

cons of mode

Answer 4

• small samples may not have a mode

- ignores most of the information in a distribution

Question 5

median

Answer 5

the score that divides the distribution in half

Question 6

median is used when

Answer 6

• variables are measured with open ended distributions

- extreme scores (outliers)

Question 7

mean

Answer 7

mean is the average

Question 8

mean pros

Answer 8

• best with interval/ratio data
• does not ignore any data
• symmetric distributions
• used in inferential statistics

Question 9

mean cons

Answer 9

• misleading for highly skewed distributions

- the number is likely not in your distribution

Question 10

variation ratio (VR)

Answer 10

VR = 1 - % of cases in the mode

Question 11

interquartile range (IQR)

Answer 11

Q3 - Q1

Question 12

what does a quartile represent

Answer 12

specific scores in the distribution
Q1 25%
Q2 50%
Q3 75%

Question 13

Q2 is the _____ value

Answer 13

median

Question 14

strengths of IQR

Answer 14

• not effected by extreme scores
• reasonably stable
• easy to compute

Question 15

weakness of IQR

Answer 15

• limited use: descriptive purposes only

- ignores the upper and lower 25%

Question 16

standard deviation (SD)

Answer 16

describes the average distance of the values from their mean

Question 17

large SD

Answer 17

• less consistency in the data

- data might be more suspect due to large degree of dispersion through the mean

Question 18

small SD

Answer 18

• more consistency in the data

- less dispersion through the mean