Concepts (CH 3): Statistical Concepts and Market Returns Flashcards

1
Q

refer to data and to the methods used to analyze data

A

statistics

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2
Q

what are the two statistical methods

A

descriptive & inferential

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3
Q

used to summarize the important characteristics of a large data set

A

descriptive

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4
Q

procedures used to make forecasts, estimates, or judgements about a large set of data on the basis of the statistical characteristics of a smaller set (a sample)

A

inferential

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5
Q

set of all possible members of a stated group

A

population

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6
Q

subset of the population of interest

A

sample

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7
Q

What are the types of measurement scales

A

nominal scales, ordinary scales, interval scales, ratio scales

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8
Q

observations are classified/ counted in no particular order (least information)

A

nominal scales

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9
Q
  • higher level of measurement than nominal scales
  • every observation is assigned to one of several categories
  • categories are ordered with respect to a specified characteristic
A

ordinary scales

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10
Q
  • provides relative ranking, like ordinary scales
  • differences between scale values are equal
A

interval scales

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11
Q

What is the weakness of the interval scale?

A

measurement of zero (0) does not necessarily indicate the total absence of what is being measures

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12
Q
  • most refined level of measurement
  • provides ranking and equal differences
    between scale values
  • have a true zero point as origin
A

ratio scales

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13
Q

measure used to describe a characteristic of a population

A

PARAMETER

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14
Q

measures characteristic of a sample

A

SIMPLE STATISTIC

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15
Q

- tabular presentation of statistical data that aids the analysis of large data sets
- summarizes statistical data by assigning
it to specified groups, or intervals
- data employes with a frequency distribution may be measured using any
type of measuryment scale

A

FREQUENCY DISTRIBUTION

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16
Q

in a frequency distribution, it is the interval with the greatest frequency

A

modal interval

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17
Q
  • useful way to present data
  • percentage of total observations falling within each interval
A

RELATIVE FREQUENCY

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18
Q

sum of the absolute or relative
frequency starting at the lower interval and progressing through the highest

A

CUMULATIVE ABSOLUTE FREQUENCY/CUMULATIVE RELATIVE FREQUENCY

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19
Q
  • graphical presentation of the absolute
    frequency distribution
  • bar chart of continuous data
  • allows us to see where most
    observations are concentrated
A

HISTOGRAM/FREQUENCY POLYGON

20
Q
  • the midpoint of each interval is plotted on the horizontal axis and the absolute frequency for that interval is plotted on the vertical axis
  • points are connected with a straight line
A

frequency polygon

21
Q
  • identify the center, or average of a data set
  • can be used to represent the typical or expected value in the data set
A

measures of central tendency

22
Q

all observed values in the population are summed and divided by the number of observations in the population

A

population mean

23
Q

sumofallthevaluesinasampleofa population divided by the number of observations in the sampler

A

sample mean

24
Q
  • most widely used measure of central tendency
  • only measure of central tendency for which the sum of the deviations from the mean is zero (0)
A

ARITHMETHIC MEAN

25
recognizes that different observations may have a disproportionate influence on the mean
WEIGHTED MEAN
26
value that occurs most frequently in a data set
MODE
27
- when a distribution has one value that appears most frequently
unimodal
28
when a set of data has two or three values that occur most frequently
bimodal or trimodal
29
is often used when calculating investment returns over multiple periods or when measuring compound growth rates
GEOMETRIC MEAN
30
- used for certain computations - such as the average cost of shares purchased over time
HARMONIC MEAN
31
uncertain quantity/number
random variable
32
an observed value of a random variable
outcome
33
single outcome or a set of outcomes
event
34
events that cannot both happen at the same time
mutually exclusive events
35
those that include all possible outcomes
exhaustive events
36
2 defining properties of probability
1. probability of occurrence of any event is between 0 and 1 2. if a set of events, E1, E2,... En, is mutually exclusive and exhaustive, the probability of those events sum to 1
37
established by analyzing past data
empirical probability
38
determined using a formal reasoning and inspection process
priori probability
39
- least formal method of developing probabilities - involves the use of personal judgment
subjective probability
40
stating the odds that an event will or will not occur is an alternative way of expressing probabilities
ODDS FOR and AGAINST the EVENT
41
- marginal probability - probability of an event regardless of the past or future occurrence of other events
unconditional probability
42
- occurrence of one event affects the other probability of the occurrence of another event
conditional probability
43
- the probability that they will both occur - can be calculated from the conditional probability that A will occur given B occurs (conditional) and the probability that B will occur (unconditional)
MULTIPLICATION RULE OF PROBABILITY
44
- used to determine the probability that at least one of the 2 events will occur - either A or B will occur
addition rule
45
- refer to events for which the occurrence of one does not influence the occurrence of the others - can be expressed in terms of conditional probabilities
INDEPENDENT EVENTS
46
- the occurrence of event A affects the probability of the occurrence of event B
DEPENDENT EVENTS