stat rev Flashcards

1
Q

Stato means?

A

Italian of State

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2
Q

The word statistics first appeared in print in
the book by

A

Gottfried achenwall

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3
Q

when was the theory of
probability utilized in relation to data

A

18600

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4
Q

is
the degree of likelihood for an event to
happen.

A

Probability

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5
Q

theory of probability has its beginnings
during the time of

A

Cardano, 1525

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6
Q

when was a certain Chevalier de Mere asked
an intriguing question that deals with
probability which provoked the fertile minds
of Blaise Pascal and Pierre de Fermat.

A

1654

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7
Q

the science of collecting, analyzing,
presenting, and interpreting data.

A

Statistics

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8
Q

Governmental
needs for ____ data as well as information about a
variety of economic activities provided much of the
early ____ for the field of statistics.

A

Census, Impetus

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9
Q

is the field of statistics that focuses on
quantitatively description of a collection
of data.
- It is usually used to define the basic
characteristics of the data in a study.

A

Descriptive statistics

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10
Q

It is used to make conclusions of the
probability that a difference between
samples is either reliable or by chance.

A

Inferential Statistics

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11
Q

describes a whole population
while a statistics described a sample of a
given population.

A

Parameter

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12
Q

a measure of “types”
and may be represented in terms of
characteristics, names, or symbols. Answer
the question “what” or “what type”

A

Qualitative Data

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13
Q

a measured of
“values”, or “counts” and expressed in
numerical values. Answer the question “how
many” and “how much”

A

Quantitative Data

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14
Q

data are in original form.

A

Raw Data

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15
Q

data collected is already
arranged in certain pattern such as in
ascending or descending order.

A

Array Data

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16
Q

are the characteristics of the
individual to be observed or measured.

A

Variables

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17
Q

– called the
predictor variable.

A

Independent Variable

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18
Q

Called the criterion Variable

A

Dependent Variable

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19
Q

– variables that
can be expressed in decimals.

A

Continuous variable

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20
Q

variables that cannot be expressed in
decimals.

A

Discrete or Discontinuous Variable

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21
Q

LEVELS OF MEASUREMENTS

A

Nominal Scale
Ordinal Scale
Interval Scale
Ratio scale

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22
Q

Data that consist of names, labels, or
categories only
The data cannot be arranged in an ordering
scheme
numbers or symbols are used to classify an
object or person to identify the group they
belong

A

Nominal Scale

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23
Q

Data contains the properties of nominal
level.
The data can be arranged in an ordering
scheme or ranked.
The difference between the values of the
data cannot be determined. The interval is
meaningless.

A

Ordinal Scale

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24
Q

Data contain the properties of ordinal
level.
Data values can be ranked.
The difference between the values of the
data are of known sizes.
The interval between the values has
meaning.
The “zero” does not imply the absence
of characteristics.
The ratio of data values are meaningless.

A

Interval Scale

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25
Data contain the properties of interval level. The “zero” indicates the absence of the characteristics under consideration The ratio of data values has meaning.
Ratio Scale
26
Uncertainty is a part of our daily lives.  The branch of mathematics that deals with uncertainty is the
Theory of Probablitity
27
number of ways 4 shows up number of ways a balance die can fall = 1 6
28
well-defined results
Experiments
29
are all equally likely or they occur by chance or randomly, it is intuitively clear that they have equal probabilities. Thus, If an experiment has “n” equally likely outcomes, then the probability of each outcomes is 1 n
Outcomes
30
P (E) =
probability of event
31
Are data collected directly by the researcher himself/herself.
Primary Data
32
Are information taken from published and unpublished materials previously gathered by other researchers or agencies such as book, newspaper, magazine, journals, published and unpublished thesis and dissertations.
Secondary Data
33
The 5 methods of data collection
Direct method Indirect Method Registration Method Observation Method Experimental Method
34
“interview method” - done through a direct and personal contact of the researcher with the person from whom data will be collected
Direct Method
35
“questionnaire method” - Executed through the use of either online questionnaire or paper form questionnaires distributed to groups of people.
Indirect Method
36
Done through the gathering of data from concerned offices. - Example: PSA; Registrar Office
Registration Method
37
Purely based on the subjective remarks of the observer. - It is applicable to data pertaining to attitude, behavior, and values of individuals.
Observation Method
38
The method that determines the cause and effect relationships of a certain parameter or event under a controlled condition. - This method is usually used by researchers in the field of sciences.
Experimental Method
39
The complete set of individuals or subjects
Population
40
Is just a representative of the whole population.
Sample
41
How to get the sample size?
n = N / 1+N(e)²
42
n = N = e = E=
n = sample size N = population e = margin of error E= Events
43
Probability sampling
1. Simple random sampling 2. Systematic sampling 3. Stratified sampling 4. Cluster sampling
44
Non-Probability sampling
1. Convinces sampling 2. Voluntary response sampling 3. Purposive sampling 4. Snowball sampling
45
often times used when the population to be considered is too large.
Restricted Random Sampling
46
There are two types of restricted random sampling:
systematic sampling and stratified sampling.
47
The selection of sample is done by picking every k element of the th population k^th = N / n
Systematic Sampling
48
Is a process or activity that generates data
STATISTICAL EXPERIMENT
49
Is an organized record of measurements arranged in columns and rows.
DATA SET
50
is a collection of one or more outcomes of an experiment.
Event ex: E = {TH, HT}
51
is the set/collection of all possible outcomes in an experiment.
SAMPLE SPACE
52
is a function that associates a real number to each element in the sample space. It is a variable whose values are determined by chance.
Random Variable
53
A random variable is a ___________________f its set of possible outcomes is countable. Mostly, discrete random variables represent count data, such as the number of defective chairs produced in a factory.
Discrete Random Variable
54
A random variable is a ___________________ it takes on values on a continuous scale. Often, continuous random variables represent measured data, such as heights, weights, and temperatures.
continuous random variable
55
EVERY UNIT HAS A ‘CHANCE’ OF BEING SELECTED, AND THAT CHANCE CAN BE QUANTIFIED.
Probability Sampling
56
EVERY ITEM IN A POPULATION DOES NOT HAVE AN EQUAL CHANCE OF BEING SELECTED.
Non Probability Sampling
57
TO PREVENT THE POSSIBILITY OF A BIAS OR ERRONEOUS INFERENCE, A RANDOM SAMPLING IS COMMONLY RECOMMENDED.
SIMPLE RANDOM SAMPLING
58
IN WHICH THE DRAWN PAPERS ARE NO LONGER RETURNED IN THE CONTAINER.
SAMPLING WITHOUT REPLACEMENT
59
INVOLVES RETURNING TO THE CONTAINER EVERY PIECE DRAWN. THIS ARRANGEMENT HOLDS THE PROBABILITY CONSTANT. THUS, IF WE HAVE 10 SLIPS OF PAPER, THE PROBABILITY OF CHOOSING ONE IN 10 IS MAINTAINED THROUGHOUT THE PROCESS.
SAMPLING WITH REPLACEMENT
60
THE ITEMS ARE ARRANGED IN SOME WAY-ALPHABETICALLY OR SOME SORT. - A RANDOM STARTING POINT IS SELECTED; AND THEN EVERY k MEMBER WILL BE THE th SUCCEEDING SAMPLES
2. SYSTEMATIC RANDOM SAMPLING
61
*A POPULATION IS FIRST DIVIDED INTO SUBSETS BASED ON HOMOGENEITY CALLED STRATA.
STRATIFIED RANDOM SAMPLING
62
*SAMPLES ARE SELECTED PROPORTIONALLY FROM EACH STRATUM WHICH CAN BE DONE THROUGH SIMPLE OR SYSTEMATIC RANDOM SAMPLING.
Stratified Random Sampling
63
CAN BE DONE BY SUBDIVIDING THE POPULATION INTO SMALLER UNITS AND THEN SELECTING ONLY AT RANDOM SOME PRIMARY UNITS WHERE THE STUDY WOULD THEN BE CONCENTRATED.
CLUSTER SAMPLING