Chapter 3

Question 1

Descriptive Statistics

Answer 1

Summarize or describe relevant characteristics of data

Question 2

Mean

Answer 2

Average

Question 3

Σx

Answer 3

Sum of all data values

Question 4

Median

Answer 4

Middle value when all data are set in numerical order (count)

Question 5

Mode

Answer 5

Value that occurs with the greatest frequency in a data set

Question 6

Bimodal

Answer 6

Two modes

Question 7

Multimodal

Answer 7

More than 2 modes

Question 8

No mode

Answer 8

No data value is repeated

Question 9

Midrange

Answer 9

Largest value+minimum data value/2

Question 10

Rounding rule

Answer 10

Round to one place greater than the data

Question 11

Nominal level data

Answer 11

Doesn’t make sense to measure center numbers

ranks, zip codes, things that aren’t measurements

Question 12

Mean from a frequency distribution

Answer 12

Sum of all class midpoints/sum of frequencies
x̅=Σ(f*x)/Σf

Question 13

x̅

Answer 13

Mean

Question 14

f

Answer 14

Frequencies

Question 15

x

Answer 15

Class midpoint for frequency distribution, value in weighted mean, frequencies in s, magic in σ

Question 16

Weighted Mean

Answer 16

data contributes more significance than another: break it down

Question 17

Weighted mean formula

Answer 17

x̅=Σ(w*x)/Σw

Question 18

Skewed distribution

Answer 18

Data plot is more on one side than the other

Question 19

Skewed to the left

Answer 19

Negatively skewed

Question 20

Skewed to the right

Answer 20

Positively skewed

Question 21

Symmetric Data

Answer 21

Zero skewness: mean, median, mode are same

Question 22

Range

Answer 22

Largest value-smallest value

Question 23

Standard Deviation for a sample (s)

Answer 23

Measure of variation of values about the mean.
s=√ nΣ(x^2)-(Σx)^2/n(n-1)
n=#values
x=frequencies

Question 24

Standard Deviation for a population (σ)

Answer 24

Measure of variation of values about the mean.
σ=√Σ(x-μ)^2/N
N=pop. size
μ=mean of pop
x=some magic # you pull out of your ass

Question 25

Variance

Answer 25

s^2, σ^2 s^2 tends to be close to σ^2, making s^2 an unbiased predictor of σ^2. But difficult to understand caz different that original unit.

Question 26

Rule of thumb

Answer 26

95% of data lies between 2 SD of the mean

Question 27

Estimate Min & max data values

Answer 27

x̅-(2s), x̅+(2s)

Question 28

Estimate SD

Answer 28

s=range/4

Question 29

Empirical rule for bell shaped

Answer 29

68% of data falls within 1SD of mead, 95% 2SD, 99.7% 3SD

Question 30

Chebyshev’s Theorum

Answer 30

For any distribution the proportion of data values lying with K SD of the mean is always at least 1-1/K^2, where K is any positive #>1
K=SD from mean

Question 31

s

Answer 31

sample SD

Question 32

σ

Answer 32

Pop. SD

Question 33

s^2

Answer 33

Sample variance

Question 34

σ^2

Answer 34

Pop. variance

Question 35

&laquo_space;SD

Answer 35

Values in data set are close together

Question 36

> > SD

Answer 36

Values in data set have large variation

Question 37

Z score (standardized value)

Answer 37

The # of SD that a given value x is above or below the mean.

z=x-x̅/s or z=x-μ/σ

Question 38

Usual z scores

Answer 38

-2 < Z SCORE < or equal to 2

Unusual data is called outlier data

Question 39

Percentiles

Answer 39

Relative position of a data value compared to the data set in 100 groups. Data is _% BELOW a #

Question 40

Percentile of x equation

Answer 40

x=100(#values below x)/(total# values)

Question 41

Quartiles

Answer 41

Divides group into 4 parts Q1=P25, Q2=P50, Q3+P75

Question 42

Interquartile range (IQR)

Answer 42

IQR=Q3-Q1

Question 43

5 number summary box plot

Answer 43

Minimum, Maximum, median, Q1, Q3

Question 44

Outliers

Answer 44

Data above Q3 or below Q1 by an amount > 1.5 IQR

Question 45

Estimate range

Answer 45

min=x̅-(2s), max=x̅+(2s) OR range=s*4

Question 46

Coefficient of variation

Answer 46

s/x̅100, σ/μ100 described sd relative to mean