Week 2 - Summarizing Data

Question 1

Scatter plot

Answer 1

allows us to visualize the nature of the relationship between 2 variables.

Question 2

linear relationship

Answer 2

when the gradient of the slope stays the same throughout

Question 3

Histogram

Answer 3

used to understand the distribution of a single numerical variable - ie how data is spread out or arranged

Question 4

mean

Answer 4

the center or typical value in a set of data. one of the most common measures of central tendency is the mean.
in a sample the mean is: x^-

Question 5

one pitfall of mean

Answer 5

its very sensitive to outliers, and they can have a huge impact on the accuracy of the result

Question 6

median

Answer 6

another measure of central tendency. median represents the middle value - it seperates the smallest 50% from the largest 50%

Question 7

standard deviation

Answer 7

this is a measure of dispersion. it tells us how far away observations may be from the mean

Question 8

interquartile range

Answer 8

the difference between the 75th percentile in a set of data and the 25th percentile
this is robust to outliers because it focuses only on the middle 50
% of data

Question 9

Box whisker plot

Answer 9

the box represents the interquartile range
the whiskers extend to 1.5 times the interquartile range

Question 10

shapes of distributions

Answer 10

one important dimension is the symmetry and skew-ness of a distribution

Question 11

different skews

Answer 11

right skewed - the mean is larger than the median
left skewed - the mean is smaller than the median

Question 12

presenting categorical data

Answer 12

this is harder, its typically summarized using counts or proportions of different outcomes

Question 13

contingency table

Answer 13

this summarizes data for 2 categorical variables