Statistics Midterm

Front 1

Observations (such as measurements, genders, survey responses) that have been collected.

Back 1

DATA

Front 2

A collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.

Back 2

STATISTICS

Front 3

The complete collection of all elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied.

Back 3

POPULATION

Front 4

The collection of data from every member of the population.

Back 4

CENSUS

Front 5

A subcollection of members selected from a population.

Back 5

SAMPLE

Front 6

Sample data must be collected in an appropriate way, such as through a process of _____ selection.

Back 6

RANDOM

Front 7

A numerical measurement describing some characteristic of a population.

Back 7

PARAMETER

Front 8

A numerical measurement describing some characteristic of a sample.

Back 8

STATISTIC

Front 9

In New York City, there are 3250 walk buttons that pedestrians can press at traffic intersections. It was found that 77% of those buttons do not work. The figure of 77% is a _____ because it is based on the entire population of all 3250 pedestrian push buttons.

Back 9

PARAMETER

Front 10

Based on a sample of 877 surveyed executives, it is found that 45% of them would not hire someone with a typographic error on their job application. That figure of 45% is a _____ because it is based on a sample, not the entire population of all executives.

Back 10

STATISTIC

Front 11

_____ consist of numbers representing counts or measurements.

Back 11

QUANTITATIVE DATA

Front 12

_____ can be separated into different categories that are distinguished by some nonnumeric characteristic.

Back 12

QUALITATIVE (OR CATEGORICAL OR ATTRIBUTE) DATA

Front 13

The weights of supermodels is an example of _____.

Back 13

QUANTITATIVE DATA

Front 14

The genders (male/female) of professional athletes is an example of _____.

Back 14

QUALITATIVE DATA

Front 15

_____ result when the number of possible values is either a finite number or a "countable" number. (That is, the number of possible values is 0 or 1 or 2, and so on.)

Back 15

DISCRETE DATA

Front 16

_____ result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps.

Back 16

CONTINUOUS (NUMERICAL) DATA

Front 17

The numbers of eggs that hens lay are _____ because they represent counts.

Back 17

DISCRETE DATA

Front 18

The amounts of milk from cows are _____ because they are measurements that can assume any value over a continuous span. During a given time interval, a cow might yield an amount of milk that can be any value between 0 gallons and 5 gallons. It would be possible to get 2.343115 gallons because the cow is not restricted to the discrete amounts of 0, 1, 2, 3, 4, or 5 gallons.

Back 18

CONTINUOUS DATA

Front 19

The _____ is characterized by data that consist of names, labels, or categories only. The data cannot be arranged in an ordering scheme (such as low to high).

Back 19

NOMINAL LEVEL OF MEASUREMENT

Front 20

Survey responses of yes, no, and undecided are an example of _____.

Back 20

NOMINAL LEVEL OF MEASUREMENT

Front 21

The colors of cars driven by college students (red, black, blue, white, magenta, mauve, and so on) are an example of _____.

Back 21

NOMINAL LEVEL OF MEASUREMENT

Front 22

Data are at the _____ if they can be arranged in some order, but differences between data values either cannot be determined or are meaningless.

Back 22

ORDINAL LEVEL OF MEASUREMENT

Front 23

A college professor assigns grades of A, B, C, D, or F. These grades can be arranged in order, but we can't determine differences between such grades. This is an example of _____.

Back 23

ORDINAL LEVEL OF MEASUREMENT

Front 24

Based on several criteria, a magazine ranks cities according to their "livability." Those ranks (first, second, third, and so on) determine an ordering. However, the differences between ranks are meaningless. This is an example of _____.

Back 24

ORDINAL LEVEL OF MEASUREMENT

Front 25

The _____ is like the ordinal level, with the additional property that the difference between any two data values is meaningful. However, data at this level do not have a natural zero starting point (where none of the quantity is present).

Back 25

INTERVAL LEVEL OF MEASUREMENT

Front 26

Body temperatures of 98.2F and 98.6F are examples of data at this _____. Those values are ordered, and we can determine their difference of 0.4F. However, there is no natural starting point. The value of 0F might seem like a starting point, but it is arbitrary and does not represent the total absence of heat.

Back 26

INTERVAL LEVEL OF MEASUREMENT

Front 27

The years 1000, 2008, 1776, and 1492 are an example of this _____. (Time did not begin in the year 0, so the year 0 is arbitrary instead of being a natural zero starting point representing "no time.")

Back 27

INTERVAL LEVEL OF MEASUREMENT

Front 28

The _____ is the interval level with the additional property that there is also a natural zero starting point (where zero indicates that none of the quantity is present). For values at this level, differences and ratios are both meaningful.

Back 28

RATIO LEVEL OF MEASUREMENT

Front 29

Weights (in carats) of diamond engagement rings (0 does represent no weight, and 4 carats is twice as heavy as 2 carats) is an example of ______.

Back 29

RATIO LEVEL OF MEASUREMENT

Front 30

Prices of college textbooks ($0 does represent no cost, and a $90 book is three times as costly as a $30 book) is an example of this _____.

Back 30

RATIO LEVEL OF MEASUREMENT

Front 31

A representative or average value that indicates where the middle of the data set is located.

Back 31

CENTER

Front 32

A measure of the amount that the data values vary among themselves.

Back 32

VARIATION

Front 33

The nature or shape of the distribution of the data (such as bell-shaped, uniform, or skewed).

Back 33

DISTRIBUTION

Front 34

Sample values that lie very far away from the vast majority of the other sample values.

Back 34

OUTLIERS

Front 35

Changing characteristics of the data over time.

Back 35

TIME

Front 36

A _____ lists data values (either individually or by groups of intervals), along with thier corresponding frequencies (or counts).

Back 36

FREQUENCY DISTRIBUTION (OR FREQUENCY TABLE)

Front 37

_____ are the smallest numbers that can belong to the different classes.

Back 37

LOWER CLASS LIMITS

Front 38

_____ are the largest numbers that can belong to the different classes.

Back 38

UPPER CLASS LIMITS

Front 39

_____ are the numbers used to separate classes, but without the gaps created by class limits.

Back 39

CLASS BOUNDARIES

Front 40

_____ are the values in the middle of the classes. Can be found by adding the lower class limit to the upper class limit and dividing the sum by 2.

Back 40

CLASS MIDPOINTS

Front 41

_____ is the difference between two consecutive lower class limits or two consecutive lower class boundaries.

Back 41

CLASS WIDTH

Front 42

_____ is found by dividing each class frequency by the total of all frequencies.

Back 42

RELATIVE FREQUENCY

Front 43

A _____ includes the same class limits as a frequency distribution, but relative frequencies are used instead of actual frequencies.

Back 43

RELATIVE FREQUENCY DISTRIBUTION

Front 44

The _____ for a class is the sum of the frequencies for that class and all previous classes.

Back 44

CUMULATIVE FREQUENCY

Front 45

The frequencies start low, reach a peak, then become low again.

Back 45

NORMAL DISTRIBUTION

Front 46

A bar graph in which the horizontal scale represents classes of data values and the vertical scale represents frequencies. The heights of the bars correspond to the frequency values, and the bars are drawn adjacent to each other (without gaps).

Back 46

HISTOGRAM

Front 47

The scale of a histogram that uses class boundaries or class midpoints.

Back 47

HORIZONTAL SCALE

Front 48

The scale of a histogram that uses class frequencies.

Back 48

VERTICAL SCALE

Front 49

A _____ has the same shape and horizontal scale as a histogram, but the vertical scale is marked with relative frequencies instead of actual frequencies.

Back 49

RELATIVE FREQUENCY HISTOGRAM

Front 50

The method of statistics that summarizes or describes the important characteristics of a set of data.

Back 50

DESCRIPTIVE STATISTICS

Front 51

The method of statistics that uses sample data to make inferences (or generalizations) about a population.

Back 51

INFERENTIAL STATISTICS

Front 52

A _____ is a value at the center or middle of a data set.

Back 52

MEASURE OF CENTER

Front 53

The _____ of a set of values is the measure of center found by adding the values and dividing the total by the number of values.

Back 53

ARITHMETIC MEAN

Front 54

NOTATION: Denotes the sum of a set of values.

Back 54

E

Front 55

NOTATION: Is the variable usually used to represent the individual data values.

Back 55

x

Front 56

NOTATION: Represents the number of values in a sample.

Back 56

n

Front 57

NOTATION: Represents the number of values in a population.

Back 57

N

Front 58

NOTATION: Is the mean of a set of sample values.

Back 58

x-bar = Ex/n

Front 59

NOTATION: Is the mean of all values in a population.

Back 59

mu (upside down h) = Ex/N

Front 60

The _____ of a data set is the measure of center that is the middle value when the original data values are arranged in order of increasing (or decreasing) magnitude.

Back 60

MEDIAN (OFTEN DENOTED BY X-TILDE)

Front 61

The _____ is the measure of center that is the value midway between the maximum and minimum values in the original data set. It is found by adding the maximum data value to the minimum data value and then dividing the sum by 2.

Back 61

MIDRANGE

Front 62

A simple rule for rounding answers is this:

Back 62

CARRY ONE MORE DECIMAL PLACE THAN IS PRESENT IN THE ORIGINAL SET OF VALUES

Front 63

MEAN OF A FREQUENCY DISTRIBUTION:
x-bar = E(f*x)/Ef

Back 63

FIRST MULTIPLY EACH FREQUENCY AND CLASS MIDPOINT, THEN ADD THE PRODUCTS / SUM OF FREQUENCIES

Front 64

WEIGHTED MEAN:
x-bar = e(w*x)/Ew

Back 64

FIRST MULITPLY EACH WEIGHT AND THE CORRESPONDING VALUE, THEN ADD THE PRODUCTS / SUM OF THE WEIGHTS

Front 65

A distribution of data is _____ if it is not symmetric and extends more to one side than the other.

Back 65

SKEWED

Front 66

A distribution of data is _____ if the left half of its histogram is roughly a mirror of its right half.)

Back 66

SYMMETRIC

Front 67

Data _____ (also called negatively skewed) have a longer left tail and the mean and median are to the left of the mode.

Back 67

SKEWED TO THE LEFT

Front 68

Data _____ (also called positively skewed) have a longer right tail, and the mean and median are to the right of the mode.

Back 68

SKEWED TO THE RIGHT

Front 69

The _____ of a set of data is the difference between the maximum value and the minimum value.

Back 69

RANGE

Front 70

The _____ of a set of sample values is a measure of variation of values about the mean.

Back 70

STANDARD DEVIATION

Front 71

Step 1: Compute the mean "x-bar"

Step 2: Subtract the mean from each individual value to get a list of deviations in the form (x-"x-bar")

Step 3: Square each of the differences obtained from Step 2. This produces numbers of the form (x-"x-bar")2

Step 4: Add all of the squares obtained from Step 3. This is the value of E(x-"x-bar")2

Step 5: Divide the total from Step 4 by the number (n-1), which is 1 less than the total number of values present.

Step 6: Find the square root of the result of Step 5.

Back 71

STANDARD DEVIATION

Front 72

Difference between the standard deviation of a sample and a population.

Back 72

INSTEAD OF DIVIDING BY N-1, DIVIDE BY THE POPULATION SIZE N.

Front 73

The _____ variance of a set of values is a measure of variation equal to the square of the standard deviation.

Back 73

VARIANCE

Front 74

NOTATION: Sample standard deviation

Back 74

s

Front 75

NOTATION: Sample variance

Back 75

s2