Deck 1: Introduction to Statistics
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Deck 1: Introduction to Statistics
1
Which of the following is more likely to be true?
A) small differences between things are associated with small amounts of error
B) large differences between things are associated with large amounts of error
C) small differences between things are probably real; large differences are probably error
D) large differences between things are probably real; small differences are probably error
A) small differences between things are associated with small amounts of error
B) large differences between things are associated with large amounts of error
C) small differences between things are probably real; large differences are probably error
D) large differences between things are probably real; small differences are probably error
D
2
Which of the following best describes the concept of "variance"?
A) change is inevitable and all around us
B) differences in measurement results
C) real fluctuations in measurement
D) a and c above
A) change is inevitable and all around us
B) differences in measurement results
C) real fluctuations in measurement
D) a and c above
B
3
Chapter 1 in your textbook focuses on:
A) the foundation of statistics
B) the application of mathematical formulas
C) strategies for studying statistics
D) all of the above
A) the foundation of statistics
B) the application of mathematical formulas
C) strategies for studying statistics
D) all of the above
A
4
Statistics are merely ways to make sense of and understand quantitative information.
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5
Any two identical measurements are sufficient to identify a constant.
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6
Estimates of error will always have error in them.
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7
Before taking a statistics course, everyone has already used statistics. Which of these is (are) an example of these statistics?
A) hash marks
B) bar graph
C) percentages
D) all of the above
A) hash marks
B) bar graph
C) percentages
D) all of the above
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8
The two basic reasons for variance are
A) estimates of error and measuring instruments
B) robustness and power
C) simple statistics and poor understanding of statistical assumptions
D) measurement inaccuracy and true differences between measurements
A) estimates of error and measuring instruments
B) robustness and power
C) simple statistics and poor understanding of statistical assumptions
D) measurement inaccuracy and true differences between measurements
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9
Foundation concepts underlying the reason for, and the use of, statistics are:
A) error and variance
B) probability and error
C) variance and probability
D) variance and chance
A) error and variance
B) probability and error
C) variance and probability
D) variance and chance
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10
The robustness of a statistic refers to
A) the ability to be calculated quickly
B) the ability to withstand violations of assumptions
C) the ability to locate error variance
D) the ability to find something that is really there
A) the ability to be calculated quickly
B) the ability to withstand violations of assumptions
C) the ability to locate error variance
D) the ability to find something that is really there
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11
There are two basic types of variance. They are:
A) constants and variables
B) error variance and real variance
C) systematic variance and random variance
D) none of the above
A) constants and variables
B) error variance and real variance
C) systematic variance and random variance
D) none of the above
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12
A constant is best characterized as:
A) a variable that only changes under certain circumstances
B) a dependable phenomenon
C) unchanging measurement
D) the absence of error
A) a variable that only changes under certain circumstances
B) a dependable phenomenon
C) unchanging measurement
D) the absence of error
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13
The power of a statistic refers to
A) the ability to withstand violations of assumptions
B) the ability to be calculated quickly
C) the ability to find something that is really there
D) the ability to locate error variance
A) the ability to withstand violations of assumptions
B) the ability to be calculated quickly
C) the ability to find something that is really there
D) the ability to locate error variance
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14
What are most statistics primarily designed for?
A) to tell us something about error
B) to provide the best measurement possible
C) to provide estimates of probability
D) to predict outcomes
A) to tell us something about error
B) to provide the best measurement possible
C) to provide estimates of probability
D) to predict outcomes
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15
The related concepts of variance and error are the backbone of statistics.
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16
Accuracy:
A) is always possible
B) always results in larger amounts of variance
C) solves all measurement problems
D) none of the above
A) is always possible
B) always results in larger amounts of variance
C) solves all measurement problems
D) none of the above
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17
A "good" statistic is characterized by which of the following?
A) provides a quick and relatively accurate "picture" of the data
B) has the ability to reduce data to the nominal level of measurement
C) requires a minimum of calculation
D) all of the above
A) provides a quick and relatively accurate "picture" of the data
B) has the ability to reduce data to the nominal level of measurement
C) requires a minimum of calculation
D) all of the above
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18
There are three general types of statistics. Which of the following is NOT one of those?
A) graphic
B) predictive
C) descriptive
D) inferential
A) graphic
B) predictive
C) descriptive
D) inferential
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19
Why do we have many kinds of statistics?
A) because of many statisticians creating tools for handling special problems
B) because of the need for different types of samples
C) it is simply a product of 200 years of historical development
D) because of the many types of error and variance
A) because of many statisticians creating tools for handling special problems
B) because of the need for different types of samples
C) it is simply a product of 200 years of historical development
D) because of the many types of error and variance
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20
The different statistics we use to tell us about variance and error have different capabilities, particularly in regard to their accuracy and ability to withstand problems in the data.
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21
Predictive statistics measure the strength of a relationship.
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22
A constant is a variable that always demonstrates a relationship with another variable.
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23
Predictive statistics are related to the explanatory phase of knowledge.
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24
Descriptive statistics are designed to describe statistical significance of a relationship.
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25
Inferential statistics are used to establish the accuracy of measurement.
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