STA013 Fall 24 Final Exam

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A _______ is a characteristic that changes or varies over time and/or for different individuals or objects under consideration

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1

A _______ is a characteristic that changes or varies over time and/or for different individuals or objects under consideration

variable

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2

An ___________________ is the individual or object on which a variable is measured

experimental unit

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3

A single ______ or data value results when a variable is actually measured on an experimental unit

measurement

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4

A _______________ is the set of all measurements of interest to the investigator

population

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5

A ______ is a subset of measurements selected from the population of interest

sample

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6

_______________ data results when a single variable is measured on a single experimental unit

univariate

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7

____________ results when two variables are measured on a single experimental unit

bivariate

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8

________ results when more than two variables are measured

multivariate

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9

___________ variables measure a numerical quantity or amount on each experimental unit

quantitative

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10

A _____________ variable can assume infinitely many values corresponding to the points on a line interval. There are no gaps

continuous

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11

When constructing a graph, we need to first construct a _________________ and then use it to create a graph called a ______________

statistical table, data distribution

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12

The sum of the relative frequencies is ______

1

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13

A ____________ is the familiar circular graph that shows how the measurements are distributed among the categories

pie chart

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14

A _______________ shows the same distribution of measurements among the categories, with the height of the bar measuring how often a particular category was observed

bar chart

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15

For a pie chart, the angle of the sector for a category = ____________ * 360

relative frequency

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16

Pie charts and bar charts are _____________ to qualitative data

not exclusive

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17

A variable can take on as many values as the numbers in an interval is called _____________ variable

continuous

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18

Time series data are most effectively presented on a ___________ with time as the horizontal axis. The idea is to try to find a pattern or __________ that will likely continue into the future

line chart, trend

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19

For a histogram, a ______ is a subinterval created when you divide up the interval from the smallest to the largest measurement

class

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20

The ________ is the difference between the upper and lower class boundaries

width

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21

The class _____________ is the number of measurements falling into that particular class

frequencies

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22

Histogram Steps
1. Choose the number of classes, usually between 5 and ______. The more data you have, the more ______ you should use

12, classes

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23

2.Find the approximate class _______ by dividing the difference between the largest and smallest values by the number of class

width

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24

3. Round the approximate class width up to a convenient number
4. If the data is discrete, you might assign one class for each integer value. For a large number of integer values, you may need to group them into classes

5.List the class boundaries. The _________ class must include the smallest measurement. Then add the remaining classes, including the left boundary point but not the right.

lowest

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25

6.Build a statistical table containing the classes, their ___, and their relative frequencies.
7. Draw the histogram like a bar graph, with the class intervals on the horizontal axis and relative frequencies as the bar height

frequency

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26

A distribution is ___________ if the left and right sides of the distribution, when divided at the middle value, form mirror images

symmetrical

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27

A distribution is _____________________ if a greater proportion of the measurements lie to the right of the peak value

skewed to the right

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28

A distribution is ___________ if it has one peak

unimodal

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29

The are three types of measures of variability: ____________, ___________, and ___________

range, variance, standard deviation

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30

The _____________ of a set of n measurements is defined as the difference between the largest and smallest measurements

range

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31

The variance of a population of N measurements is the average of the squares of the ____________ of the measurements about their mean μ

deviations

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32

The variance of a sample of n measurements is the sum of the ______ of the measurements about their mean _______ divided by _________

squares, |x (x bar), n-1

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33

The measures of variability can be negative. This statement is ________

false

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34

If the measure of variability is equal to zero, all the data should have ____________

the same value

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35

The range and standard deviation have the same _________ as the original data

unit

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36

By Tchebysheff's Theorem, given a number k greater than or equal to 1 and a set of n measurements, at least ________ of the measurements will lie within k _________ of their mean

1-(1/k)^2, standard deviation

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37

Suppose μ is the population mean and σ is the standard deviation. Answer the following questions using Tchebysheff's Theorem:
a. At least none of the measurements lie in the interval μ__σ to μ__σ
b. At least 3/4 of the measurements lie in the interval μ__σ to μ__σ
c. At least 8/9 of the measurements lie in the interval μ__σ to μ__σ

a. -1, +1
b. -2 , +2
c. -3 ,+3

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38

If the data is ____________, we have
The Empirical rules
a. The interval ( μ+/-σ ) contains approximately ______% of the measurements
b. The interval (μ+/-2σ) contains approximately _____% of the measurements
c. The interval (μ+/-3σ) contains approximately _________ of the measurements

mound shaped
a. 68
b. 95
c. 99.7

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39

The empirical rule requires the distribution to be ____________. Tchebysheff's theorem does not require anything

Unimodal

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40

Measure of center is a measure along the ____________ that locates the _____ of the distribution

horizontal axis, center

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41

There are three different measures: __________, __________, ____________

mean, median, mode

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42

Arithmetic mean is the sum of data points of interest divided by ___________. For population, we use notation ________. For sample, we use notation _________

total number of data points, mew (μ), |x (x bar)

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43

The ___________ m of a set of n measurements is the value of x that falls in the middle position when the measurements are ordered from _______ to __________

median, largest, smallest

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44

Mean and median ____________ coincide with each other. We can use them to infer the shape of the distribution

do not always

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45

When the distribution is ________, mean and median are the same

symmetric

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46

When the distribution is skewed to the right, mean is ___________ than the median

larger

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47

when the distribution is skewed to the left, mean is __________ than the median

smaller

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48

The _______________ is the category that occurs most frequently, or the most frequently occurring value of x

mode

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49

Mode is generally used to describe a ________ dataset

large

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50

Mean and median can be used for both ________ and _______ datasets

large, small

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51

It is _____________ to have more than one mode in the dataset

possible

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52

Do we want more or less variability in the data in the following examples?
a. the lifetime of machines produced by a company
b. The SAT score

a. less
b. more

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53

Measures of __________ can help you create a mental picture of the spread of the data

variability

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54

The lower quartile (first quartile) Q1, is the value of x that is greater than ______ of the measurements and is less than the remaining _________

25%, 75%

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55

The second quartile is the ________

median

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56

The upper quartile (third quartile) Q3, is the value of x that is greater than ______ of the measurements and is less than the remaining _________

75%, 25%

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57

The interquartile range for a set of measurements is the difference between the ___________ and ______________

third quartile, first quartile

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58

We can use five numbers to summarize the data: _____________, _______, _________, ________, and __________

minimum, Q1, median, Q3, maximum

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59

Box-plot can be used to detect ________

outliers

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60

An ___________ is the process by which an observation (or measurement) is obtained

experiment

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61

A ___________ is the outcome observed on a single repetition of an experiment

simple event

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62

Experiment: Toss a die and observe the number on the upper face. List the simple events in the experiment:

1, 2, 3, 4, 5, 6

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63

An _________ is a collection of simple events.

Event

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64

Two events are _________________ if, when one event occurs, the other cannot, and vice versa

mutually exclusive

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65

Simple events are all mutually exclusive (true/false)

true

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66

The set of all simple events is called the __________

sample space

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67

Some experiments can be generated in stages, and the sample space can be displayed in a ______________

tree diagram

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68

If you repeat the experiment more and more times, n becomes larger and larger, eventually, you generate the entire population. In this population, the _________________ of the event A is defined as the probability of event A

relative frequency

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69

Each probability must lie between ____ and ____

0, 1

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70

The sum of the probabilities for all _____________ in S, the sample space equals 1

simple events

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71

The probability of an event A is equal to the sum of the probabilities of the _______________ contained in A

simple events

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72

How to calculate the probability of an event
1. List all the ___________ in the sample space

simple events

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73

How to calculate the probability of an event
2. Assign an appropriate ________ to each simple event

probability

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74

How to calculate the probability of an event
3. Determine which simple events result in the __________ of interest

event

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75

How to calculate the probability of an event
4. ____________ the probabilities of the simple events that result in the event of interest

sum

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76

What are the three rules for counting the number of simple events?
1. The ________ rule

mn

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77

What are the three rules for counting the number of simple events?

2. A counting rule for ____

permutations

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78

What are the three rules for counting the number of simple events?
3. A counting rule for ______________

combinations

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79

Z-score is a measurement of _______________

relative standing

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80

Z-score measures the distance between a particular observation x and the ________, measured in units of ____________. Its formula is z=measurement-mean/standard deviation

mean, standard deviation

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81

A percentile is another measure of relative standing, most often used for __________ data sets

large

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82

The p-th percentile is the value of x that is greater than __________% of the measurements and is less than the remaining ________%

p, 100-p

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83

When the ordering or arrangement of the objects is important, you can use a counting rule for ________

permutations

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84

Sometimes the ordering or arrangement of the objects is not important, but only the objects that are chosen. In this case, you can use a counting rule for ____________

combinations

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85

The ________ of events A and B, denoted by A ∪ B, is the event that either A or B both occur

union

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86

The ___________ of events A and B, denoted by A ∩ B, is the event that both A and B occur

intersection

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87

The _________ of an event A, denoted by A^c, is the event that A does not occur

complement

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88

Simple events are mutually exclusive (true/false)

true

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89

Event A and its complement are mutually exclusive no matter what A is (true/false)

true

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90

Are mutually exclusive events independent (yes/no)

no

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91

Are two independent events mutually exclusive (yes/no)

no

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92

A _____________ (type ___ error) is the even t that the test is positive for a given condition, given that the person does not have the condition

false positive, I

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93

A ______________ (type _____ error) is the event that the test is negative for a given condition, given that the person has the condition

false negative, II

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94

A variable X is a __________________ if the value that it assumes, corresponding to the outcome of an experiment, is a chance or random event

random variable

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95

Quantitative variables are classified as either ___________ or ______________, according to the values that X can assume

discrete, continuous

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96

We defined probability as the limiting value of the _______________________ as the experiment is repeated over and over again

relative frequency

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97

Now we define the probability distribution for a random variable X as the ____________________ distribution constructed for the entire population of measurements

relative frequency

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98

The ________________ for a discrete random variable is a formula, table, or graph that gives all the possible values of X, and the probability p(x)=P(X=x) associated with each value x

probability distribution

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99

Requirements for a Discrete Probability Distribution
A. __________ </= p(x) </= _________
B. Sum of x p(x) = _______

A. 0, 1
B. 1

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100

Comparative relative frequency distribution and probability distribution: the difference is that the relative frequency distribution describes a ________ of n measurements, while the probability distribution is constructed as a model for the entire __________ of measurements

sample, population

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