Chapter 2

Question 1

What are the two types of variables?

Answer 1

1) Categorical. 2) Quantitative.

Question 2

Categorical Variable

Answer 2

These variables that sort and organize the data into different categories or classifications are called categorical variables.

Question 3

T/F One categorical variable will have multiple categories

Answer 3

True.

Question 4

Name the variable and the categories for the following:

sex(male or female.)

Answer 4

Sex is the categorical variables. Categories are female and male.

Question 5

Quantitative variables

Answer 5

Numerical data that gives us some quantity is called quantitative.

Question 6

T/F All quantitative variables are numeric, but not all numeric variables are quantitative.

Answer 6

True. If you can take an average, its probably quantitative. If not, its likely categorical.

Question 7

What are the two types of quantitative variables?

Answer 7

1) Continuous

2) Discrete.

Question 8

Continuous variables

Answer 8

Can take on any value within an interval, and there is no theoretical distance between two observable values. Ex: Height, Weight, Temperature.

Question 9

Discrete Variable

Answer 9

Has a minimum distance between its measurements. 4 births, 5 births, 6 births. Number of students in a class.

Question 10

Frequency

Answer 10

Simply means the number of occurrences of a categorical variable. 12 students had red hair.

Question 11

Bar Graph

Answer 11

Displays categorical varibles. Categories on horizontal axis. Frequencies on the vertical axis.. Height of rectangles are equal to the category’s frequency.

Question 12

Pie Chart

Answer 12

Displays categorical data in terms of percentages of a circle.

Question 13

What are the weaknesses of pie charts.

Answer 13

If a subject can fall into more than one category, the chart can sum up to more than 100 percent. If there are too many categories, it can be difficult to determine which slices are relatively larger.

Question 14

Contingency Table

Answer 14

Shows how two categorical variables relate to each other. Country and regional food preferences.

Question 15

Conditional Distribution

Answer 15

Restricts categorical variables to show distribution for just the cases that satisfy a certain condition. For instance murdered and not murdered.

Question 16

Dot Plot

Answer 16

Most simplistic way to display quantitative data. Displays dots which represent values and stack up on values on the x axis.

Question 17

Histogram

Answer 17

A graph that uses bars to portray the frequencies of the possible outcomes of a quantitative variable. Y is observations within a certain range. X axis ranges of values a variable can take. IQ frequencies for 7th graders.

Question 18

Distribution

Answer 18

The layout of a quantitative datasets. The curve of distributions

Question 19

Modalitity

Answer 19

Mode is the high point(s) or most frequent observations.

Question 20

Unimodal

Answer 20

Has only one high point

Question 21

Bimodal

Answer 21

Two high points.

Question 22

Uniform

Answer 22

Relatively flat data with no peaks.

Question 23

Symmetric

Answer 23

Quantitative distributions are close to mirror images of each other

Question 24

Skewed Left

Answer 24

Distribution has a long left tail. Many high observations but few low observations.

Question 25

Skewed right

Answer 25

Long right tail. Many low observations, but few high observations.

Question 26

Mean

Answer 26

Sum of the observations divided by the number of observations.

Question 27

Median

Answer 27

The point that splits the data in two half of the observations are below it, half of the observations are above it.

Question 28

T/F The mean is resistant to extreme values of skewness, while the median is sensitive to extreme values in the data

Answer 28

False, the MEDIAN is generally resistant to extreme values in the data. The MEAN is sensitive to extreme values in the data set.

Question 29

Range

Answer 29

The difference between the smallest and largest observations. No resistant to extreme values by definition.

Question 30

Standard Deviation

Answer 30

How far observations in the data set typically fall from the mean. Distance of a data point from the mean.

Question 31

Variance

Answer 31

Square of the standard deviation.

Question 32

T/F Standard deviation and variance are not resistance to outliers

Answer 32

True.

Question 33

Standard deviation pample

Answer 33

s

Question 34

Standard deviation population

Answer 34

o

Question 35

Variance Sample

Answer 35

s^2

Question 36

Variance Population

Answer 36

o^2

Question 37

Sample Size

Answer 37

n

Question 38

Population Size

Answer 38

N

Question 39

Empirical Rule

Answer 39

If a distribution is b ell shaped then approximately: 1) 68 percent of the observations fall within one standard deviation of the mean. 2) 95 Percent of observations fall within 2 standard deviations of the mean. 3) Nearly all observations fall within 3 standard deviations of the mean.

Question 40

The pth percentile

Answer 40

The percentage of observations such that p percent fall at or below that value. 90th percentile SAT.

Question 41

Quartiles

Answer 41

25 percent is the first quartile. 50 percent second quartile (median 75 percent is the third quartile.

Question 42

Interquartile Range

Answer 42

Distance between Q1 and Q3

Question 43

T/F The interquartile Range is not resistance to skewness and extreme values

Answer 43

False, it is resistant to skewness and extreme values because it only looks at values surrounding the median.

Question 44

Outleier

Answer 44

Is an unusually small or unusually large observation.

Question 45

How do you flag a observation as being an outlier.

Answer 45

An observation is an outlier if the following are true. Q1-1.5 less than or Q32+1.5IQR greater than.

Question 46

Outlier Check 2

Answer 46

Any observation that falls 3 standard deviations above or below the mean.

Question 47

Five number summary of a data set.

Answer 47

1) minimum value. 2) First quartile, 3) Median 4) 3rd quartile 5) Maximum value.

Question 48

Box Plot

Answer 48

Graphical depiction of the 5 number summary.

Question 49

T/F Use mean and standard deviation only for reasonably symmetric distribution

Answer 49

True. Otherwise use five-number summary.

Question 50

Match the Following: Standard Deviation Mean IQR Median

Answer 50

Use mean and stanard deviation together since they are not resistant to skewness and extreme values. Use only for unimodal and symmetric data sets. Use median and IQR for skewed or non unimodal data. Resistant to skewness and extreme values.

Question 51

Sid by SIde Boxplots

Answer 51

Compare two or more groups on a quantitative variable.

Question 52

Z Score

Answer 52

The score of an observation tells us how many standard deviations the observation falls from the mean. z= observation-mean/standard deviation- observation-x/s Neg if below mean pos it above mean. If greater than 3 or less than -3 then it is an outlier.

Question 53

Variable

Answer 53

any characteristics observed in a study.

Question 54

Pareto Chart

Answer 54

Bar graph from highest to lowest frequency.

Question 55

Pareto Principle

Answer 55

That a small subset of categories often contain the most observations.

Question 56

Time Series

Answer 56

Data set collected over time

Question 57

Time Plot

Answer 57

Charts each observation on the vertical scale against the time it was measured on the horizontal scale. Ex Population over time.