Chapter 2

Question 1

frequency distribution

Answer 1

records number of times each possible thing occurs during an experiment

Question 2

histogram

Answer 2

groups adjacent values together to give a visual picture, obscuring noise while preserving important data trends, looks like bar graph

Question 3

real lower limit

Answer 3

smallest value that would be classed as falling into the interval, like rounding

Question 4

real upper limit

Answer 4

largest value that would be classed as being in the interval, like rounding

Question 5

midpoint

Answer 5

average of the upper and lower limit presented for convenience

Question 6

outlier

Answer 6

extreme value that is widely separated from the rest of the data, frequently representing errors in recording data (but not always)

Question 7

normal curve

Answer 7

bell-shaped curve that is symmetrical around the center of the distribution

Question 8

kernel density plot

Answer 8

pays no attention to mean and standard deviation, instead holds to the idea that each observation might have been slightly different

Question 9

stem-and-leaf display

Answer 9

Tukey, exploratory data analysis, helpful for comparing 2 different distributions

Question 10

leading digits

Answer 10

most significant digits, form the stem (vertical axis) of the stem-and-leaf display

Question 11

stem

Answer 11

vertical axis of the stem-and-leaf display, formed by the leading digits/most significant digits

Question 12

trailing digits

Answer 12

less significant digits, form the leaves (horizontal elements) of the stem-and-leaf display

Question 13

leaves

Answer 13

horizontal elements of the stem-and-leaf display, formed by the trailing digits/less significant digits

Question 14

bimodal

Answer 14

graph having two predominant peaks instead of one (even when these peaks are not exactly the same height)

Question 15

unimodal

Answer 15

distribution having only one major peak

Question 16

modality

Answer 16

refers to the number of major peaks in a distribution

Question 17

negatively skewed

Answer 17

distribution with tail going out to the right (they point to the negative)

Question 18

positively skewed

Answer 18

distribution with tail going out to the left (they point toward the positive)

Question 19

skewness

Answer 19

statistical measures of the degree of asymmetry

Question 20

kurtosis

Answer 20

the relative concentration of scores in the center, the upper and lower ends (tails) and the shoulders (between the center of the tails) of a distribution

Question 21

mesokurtic

Answer 21

a normal distribution, with tails normally proportioned (neither too thick nor too thin) and with center normally shaped (neither too many nor too few scores concentrated there)

Question 22

platykurtic

Answer 22

flatter-shaped distribution where scores are concentrated in the shoulders (pulled in from the tails and down from the center)

Question 23

leptokurtic

Answer 23

distribution with higher-than-normal center peak and thicker-than-normal tails

Question 24

sigma

Answer 24

standard notation for sum (adds up to)

Question 25

measures of central tendency

Answer 25

different statistics that measure the "center" of the distribution

Question 26

measures of location

Answer 26

reflect where on the scale the distribution is centered

Question 27

mode

Answer 27

Mo-most common score, advantage: represents the largest number of people & unaffected by extreme scores

Question 28

median

Answer 28

Mdn-corresponds to the point at or below which 50% of the scores fall when the data are arranged in numerical order, advantage: unaffected by extreme scores

Question 29

median location

Answer 29

(N+1)/2

Question 30

mean

Answer 30

X bar, sum of scores divided by # of scores, disadvantage: influenced by extreme scores, value may not actually exist in the data; advantage: can be manipulated algebraically, estimates the population well

Question 31

relation of measures of central tendency to one another

Answer 31

whenever the distribution is normal (unimodal and symmetric), the mean, median, and mode will all be close to one another

Question 32

trimmed means

Answer 32

means calculated on data for which we have discarded a certain percentage of the data at each end of the distribution, to weaken the effects extreme scores have on the mean and to use a population estimate with a small standard of error

Question 33

dispersion

Answer 33

variability around the central measure of tendency (usually around the mean)

Question 34

range

Answer 34

measure of distance from lowest to highest score, relies on the extremes and so may be a distorted picture of the variability

Question 35

interquartile range

Answer 35

discards upper and lower 25%ages of scores, leaving middle half to make up the range (Q3-Q1), can discard too much of the data to be good representative of a sample

Question 36

first quartile

Answer 36

point that cuts off the lowest 25% of a distribution, Q1

Question 37

third quartile

Answer 37

point that cuts off the upper 25% of a distribution, Q3

Question 38

second quartile

Answer 38

median of a distribution, Q2

Question 39

Winsorized sample

Answer 39

using trimmed samples to estimate variability, dropping a %age of the highest and lowest scores and replacing them with copies of the highest and lowest remaining scores

Question 40

absolute value

Answer 40

positive expression of an integer (for example, the absolute value of -3 is 3.)

Question 41

mean absolute deviation

Answer 41

turning all numbers into their absolute values (eliminating negative numbers) prior to finding the mean to determine deviation from the mean

Question 42

standard deviation

Answer 42

sum of all (X-Xbar), squared divided by N-1

Question 43

sample variance

Answer 43

(s squared), part of the whole population

Question 44

population variance

Answer 44

(sigma squared), whole population

Question 45

coefficient of variation

Answer 45

CV=(standard deviation / mean) X 100, to express the answer as a percentage; to determine which of two groups/tests is better

Question 46

statistics

Answer 46

characteristics of samples, designated by Roman letters

Question 47

parameters

Answer 47

characteristics of populations, designated by Greek lettes

Question 48

population mean

Answer 48

symbolized by the Greek mu

Question 49

expected value

Answer 49

long-range average of many samples

Question 50

unbiased estimate

Answer 50

estimator whose expected value equals the parameter to be estimated

Question 51

degrees of freedom

Answer 51

df: losing one degree of freedom (dividing by N-1 instead of just by N) because mu is not known and must be estimated from the sample mean

Question 52

boxplot

Answer 52

aka box-and-whisker plot-method of looking at data, designed by Tukey, includes a scale that covers the whole range of obtained values, a rectangular box drawn from Q1 to Q3 with a vertical line representing the median, and lines called whiskers from the quartiles out to the adjacent values

Question 53

quartile location

Answer 53

taking the 1st and 3rd quartiles, (median location +1)/2

Question 54

inner fences

Answer 54

point that falls 1.5 times the interquartile range below or above the appropriate quartile

Question 55

adjacent values

Answer 55

those actual values in the data that are no more extreme (no farther from the median) than the inner fences

Question 56

deciles

Answer 56

like quartiles, but divide the distribution into 10ths rather than quarters

Question 57

percentiles

Answer 57

divide the distribution into hundredths

Question 58

quantiles/fractiles

Answer 58

dividing data into chunks for statistical purposes, like percentiles

Question 59

linear transformations

Answer 59

multiplying a value by a constant and adding a constant to express the same value in a new way (like converting Celsius degrees into Fahrenheit degrees)

Question 60

nonlinear transformations

Answer 60

using exponents, logarithms, trigonometric functions, etc. to transform values into another expression, usually involve a change in shape of a distribution

Question 61

centering

Answer 61

subtracting sample mean from all of the observations, rendering the new mean 0.00 but not affecting the standard deviation or the variance

Question 62

reflection

Answer 62

preventing subjects from simply checking the same point on the scale all the way down without thinking by reversing the phrasing of the questions (half could be positive, like "strongly agree", and half could be negative, like "strongly disagree"), accomplished by a linear transformation

Question 63

deviation scores

Answer 63

employed to rescale data, subtracting mean from each observation

Question 64

standard scores

Answer 64

creating deviation scores and then dividing them by the standard deviation

Question 65

standardization

Answer 65

creating standard scores from raw scores