Chapters Two-Eight: Vocabulary

Question 0

The What

Answer 0

The variables (or labels)

Question 1

The Who

Answer 1

The subject(s)

Question 2

Quantitative Variables

Answer 2

Data that is measured in units

Question 3

Area Principle

Answer 3

The area populated by a part of the graph that corresponds to the magnitude of the value it represents.

Question 4

Marginal Distribution

Answer 4

The frequency distribution of one of the variables in a margin.

Question 5

Conditional Distribution

Answer 5

The distribution of one variable for just those cases that satisfy a condition on another variable.

Question 6

Distribution

Answer 6

1) gives the possible values of a variable

2) relative frequency of each value

Question 7

Area Principle

Answer 7

Each data value should be represented by the same amount of area.

Question 8

Categorical data condition

Answer 8

Displaying and describing categorical data.

Question 9

Contingency Table

Answer 9

Displays counts and, sometimes, percentages of individuals falling into named categories of two or more variables.

Question 10

Simpson’s Paradox

Answer 10

When averages are taken from different groups and they appear to contradict the overall averages.

Question 11

How do you describe the shape of a histogram?

Answer 11

1) distinguish how many modes
2) determine whether it’s symmetrical or skewed
3) find any outliers or gaps

Question 12

Mode

Answer 12

The hump or high point in a histogram. It can be bimodal or unimodal.

Question 13

Uniform

Answer 13

Distribution that is basically even.

Question 14

Median

Answer 14

The middle value of data. Normally used for a skewed graph with the interquartile range.

Question 15

Range

Answer 15

The difference between between the maximum and minimum.

Question 16

Interquartile Range

Answer 16

Difference between the first and third quartiles.

Question 17

What does the 5-Number Summary describe?

Answer 17

The minimum, Q1, the median, Q3, and the maximum

Question 18

Mean

Answer 18

Found by summing all of the data by dividing by the count

Question 19

Variance

Answer 19

The sum of squared deviations from the mean, divided by n-1

Question 20

Standard Deviation

Answer 20

Usually reported with the mean. It is the square root of the variance.

Question 21

Outlier

Answer 21

Any point more than 1.5 IQR from either end of the box in a box plot.

Question 22

Far Outlier

Answer 22

If a point is 3.0 IQR from either end of the boxplot

Question 23

Standardizing

Answer 23

Used to eliminate units. Standardized values can be compared even if the original variables had different units.

Question 24

How do you find a standardized value?

Answer 24

By subtracting the mean an dividing by the standard deviation.

Question 25

Shifting

Answer 25

Adding a constant to each data value adds the same constant to the mean, median, and quartiles. It does not change the standard deviation or IQR.

Question 26

Rescaling

Answer 26

Multiplying each data value by a constant mulitplies both the measures of position and the measures of spread.

Question 27

Parameter

Answer 27

A numerically valued attribute of a model.

Question 28

What does a z-score tell?

Answer 28

How many standard deviations a value is from the mean.

Question 29

Nearly Normal Condition

Answer 29

The model is unimodal and symmetric.

Question 30

What does the association of a plot show?

Answer 30

1) direction
2) form
3) strength

Question 31

Correlation Coefficient

Answer 31

“r” is a numerical measure of the direction and strength of a linear association.

Question 32

Lurking Variable

Answer 32

A variable other than x and y that simultaneously affects both variables, accounting for the correlation between the two.

Question 33

Predicted Value

Answer 33

“y” found for a given x-value in the data. The predicted values (x, ^y) all fit exactly on the line.

Question 34

Residuals

Answer 34

The predicts value subtracted by the original value.

Question 35

Regression to the Mean

Answer 35

Because the correlation is always less that 1.0, the predicted ^y tends to be fewer standard deviations from its mean than “x” was from its mean.

Question 36

Line of Best Fit

Answer 36

Housetop y = B(of 0) + (B(of 1) • x)
B(of 0) = y-intercept
B(of 1) = slope

Question 37

Slope

Answer 37

Given in “y-units per x-unit.” Changes of one unit in x are associated with changes of of B(of 1).