Categorical and Quantitative Variables

Question 1

Quantitative vs Categorical

Answer 1

Quantitative - numerical value - can report the average of all individuals.

Categorical - can be categorized - can report the count or proportion of individuals with that characteristic.

Question 2

Individuals vs Variable

Answer 2

Individuals - each data point - objects described in a set of data.

Variable - cartelistic describes data - property that characterizes an individual.

Question 3

Discrete vs Continuous

Answer 3

For Quqntatative Data

Discrete - whole number (#of cars owned, cannot own 1/2 a car)

Continuous - ex. age can be 60 years and 5 days

Question 4

Histograms - summary graph for ____
useful to understand ___

Answer 4

a single variable -
understand the pattern of variability in the data, especially for large data sets.

Question 5

Steps to make a Histogram

Answer 5

1) The range of values that the quantitative variable takes is divided into equal-size intervals, or classes. (Horizontal Axis)

2) The vertical axis represents either the frequency (counts) or the relative frequency (percents of total).

3) For each class on the horizontal axis, draw a column. The height of the column represents the count (or percent) of data points that fall in that class interval.

• Can be either frequency (count of guinea pigs) or percent (relative frequency) - both have identical shape

Need to chose classes - not to many with 0 or 1 counts, not so detailed that is no longer summery but not so summarized that you loose info.

Question 6

Histogram Shape

Answer 6

Symmetric, L skew R skew

Unimodal, bimodal - one vs two “humps”

Question 7

Histogram Center

Answer 7

find average of data - mean median - approximate center of mass of data

Question 8

histogram Spread

Answer 8

Range of data values (ex. age 0-80)

Question 9

histogram outliers

Answer 9

data point not follow overall pattern of data - large gape in the distribution is sign of an outlier

Question 10

Dot plots and stem plots - graphs for ___

useful to___

Answer 10

the raw data -

useful to describe the pattern of variability in the data, especially for small data sets

Question 11

Stem Plot -

Answer 11

separate into a stem (first digit) and a leaf (remaining digit)

Question 12

Dot Plot -

Answer 12

represent each data point as a dot

Question 13

Line graphs: when ____

Answer 13

time plots
when there is a meaningful sequence, like time.

Data collected over time - Look for a possible:
a) Trend - a clear overall pattern (overall up in image)

b) Cyclical Variations - variations with some regularity over time (up and down in image)

Question 14

Nominal vs Ordinal

Answer 14

In Categorical Data

Nominal - purely qualitative - cannot be ordered (M or F)

Ordinal - can be ranked/ordered (ex. movie rating 1-5 stars 5>1 in goodness)

Question 15

Bar Graph

Answer 15

Each characteristic, or level, is represented by a bar. - can show many Q at a time

Frequency - the height of a bar represents either the count of individuals with that characteristic.

Relative Frequency - percent of individuals with that characteristic.

Question 16

Pie Chart -

Answer 16

can only represent how one categorical variable breaks down into its components. - only one Q at a time

Question 17

Raw data vs Frequency table

Answer 17

Raw data - whole data
Frequency table - summary statistics