Stats (3rd Quarter) Flashcards
(96 cards)
1
Q
It is a mathematical concept used to measure the occurrence of statistical events.
A
Probability
2
Q
It is the chance of a certain event will occur
or happen.
A
Probability
3
Q
Comes from the Latin word “Status” or Italian word “Statistia” or German word “Statistik” or the French word “Statistique”; meaning a political state, and originally meant information useful to the state, such as information about sizes of the population (human, animal, products, etc.)
A
Statistics
4
Q
A science that studies data to be able
to make a decision.
A
Statistics
5
Q
A science involves the methods of collecting, processing, summarizing and analyzing data in order to provide answers or solutions to an inquiry
A
Statistics
6
Q
Statistics as a Tool in Decision-Making it enable us to:
A
- Characterize persons, objects, situations, and phenomena;
- Explain relationships among variables;
- Formulate objective assessments and comparisons; and,
more importantly - Make evidence-based decisions and predictions.
7
Q
Provides information only about collected data and does not draw inferences or conclusions about a larger set of data.
A
Descriptive Statistics
8
Q
used when one makes a decision, estimates prediction or generalization about a population based on a sample.
A
Inferential Statistics
9
Q
The collection or set of units or entities from whom we got the data
A
Universe
10
Q
Is a characteristic that is observable or
measurable in every unit of the universe
A
Variable
11
Q
Set of all possible values of a variable
A
Population
12
Q
A subgroup of a universe or of a population
A
Sample
13
Q
The information we asked from the respondents.
A
Variable
14
Q
A characteristic that is observable or
measurable in every unit of the universe.
A
Variable
15
Q
It is referred to as categorical
variables such as:
sex (male or female),
religion,
marital status,
region of residence,
highest educational attainment,
etc.
A
Qualitative
16
Q
____ data answer
questions “what kind.”
A
Qualitative
17
Q
Otherwise called as numerical
data, whose sizes are
meaningful.
A
Quantitative
18
Q
It answer questions such as
“how much” or “how many”.
A
Quantitative
19
Q
____ variables have
actual units of measure.
A
Quantitative
20
Q
____ data may be
classified to as discrete or
continuous.
A
Quantitative
21
Q
are those data that can be counted that
includes whole numbers or integers,
example: the number of days, the ages
of survey respondents, and the number
of patients in a hospital.
A
Discrete
22
Q
are those that can be measured that
includes fractions and decimals,
example. height of a survey
respondent and the volume of some
liquid substance.
A
Continuous
23
Q
According to NATURE, ____ is obtained from variables which are in the form of numbers.
A
Quantitative or numerical data
24
Q
According to NATURE, ____ is obtained from variables which are in the form of categories,characteristics, names or labels.
A
Qualitative or categorical data
25
According to ARRANGEMENT, ____ is the data without any specific order or arrangement. They are referred to as raw data.
Ungrouped data
26
According to ARRANGEMENT, ____ is the data that are arranged or tabulated and presented in an organizedmanner
Grouped data
27
According to SOURCE, ____ it is the first-hand information. Example: Data gathered from a survey, where the person who collected the data is the one using it.
Primary data
28
According to SOURCE, ____ is the second-hand information. Example: Information from newspapers or journals, economics indicators. The data being used are collected by another person or organization.
Secondary data
29
It uses any or combination of the five senses (sense of sight, touch, hearing, taste and smell) to measure the variable.
Subjective method
30
____ obtains data by getting responses through a questionnaire.
Objective method
31
It obtained through the ___________________ by other entities for certain purposes.
use of existing records or data collected
32
3 Types of interviews conducted for data collection
1. Telephone interviews
2. Face-to-face interviews
3. Computer-assisted personal interviewing (CAPI)
33
Data presentation (3)
1. Textual
2. Tabular
3. Graphical
34
Presenting Data in the form of words, sentences and paragraphs.
Textual
35
Detailed information are given. It involves enumerating important characteristics, emphasizing significant figures and identifying important features of data.
Textual
36
Numerical values are presented using tables.
Tabular
37
Information are lost in tabular presentation of data.
Tabular
38
The usual tabular form of presenting the distribution of the data.
frequency distribution table
39
A visual representation of data statistics-based results using graphs, plots, and charts.
Graphical
40
Levels of measurement (4)
Nominal
Ordinal
Ratio
Interval
41
Measurement arises when we have variables that are categorical and non-numeric or where the numbers have **no sense of ordering**.
Nominal
42
This level ordering is important, that is the values of the variable could be ranked.
Ordinal
43
These scales have no absolute values–all that we can say is that one person is higher or lower in rank without stating how much greater or less.
Ordinal
44
The data can be categorized and ranked
It tells us that one unit differs by a certain amount of degree from another unit. Can state how much unit differs from another.
Interval
45
No absolute zero.
Interval
46
The data can be categorized and ranked.
There is an existence of zero
Ratio
47
It is how likely something is to happen. "chance"
Probability
48
It is a way to map outcomes of a statistical experiment determined by chance into numbers.
Random Variable
49
It is an activity that will produce outcomes, or a process that will generate data. The outcomes have a corresponding chance of occurrence.
Statistical Experiment
50
It helps model random phenomena
Random Variable
51
It is used to model outcomes of random processes that cannot be predicted deterministically in advance (but the range of numerical outcomes may, however, be reviewed).
Random Variable
52
These are random variables that can take on a finite number of distinct values.
Discrete Random Variables
53
These are random variables that take an **infinitely** uncountable number of possible values, typically measurable quantities.
Continuous Random Variables
54
2 Types of Random Variables
Discrete Random Variables
Continuous Random Variables
55
The collection of information from a sample of individuals through their responses to questions.
Survey
56
It is a method of systematically gathering information on a segment of the population such as individuals, families, wildlife, farms, business firms, and unions of workers, for the purpose of quantitative descriptors of the attributes of the population.
Sample Survey
57
Need for Sampling (5):
Cost
Timeliness
Accuracy
Detailed Information
Destructive Testing
58
A sample often provides useful and reliable information at a much lower cost than a census.
Cost
59
A sample usually provides more timely information because fewer data are to be collected and processed. This attribute is particularly important when information is needed quickly.
Timeliness
60
A sample often provides information as accurate, or more accurate, than a census, because data errors typically can ba controlled better in small tasks.
Accuracy
61
More time is spent in getting detailed information with sample surveys than with censuses.
Detailed Information
62
When a test involves the destruction of an item, sampling must be used.
Destructive Testing
63
involves random selection, allowing you to make strong statistical inferences about the whole group. It means every member of the target population has the opportunity to be included in the sample.
Probability Sampling
64
involves **non-random selection** based on convenience or other criteria, allowing you to easily collect data. This means that **not every member of the population is given the chance** to be part of the sample.
Non-probability Sampling
65
Basic Types of Probability Sampling (5):
1. Simple Random Sampling
2. Stratified Sampling
3. Systematic Sampling
4. Cluster Sampling
5. Multistage Sampling
66
is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.
Simple Random Sampling
67
It is an extension of simple random sampling which allows for different homogeneous groups, called **strata**, in the population to be represented in the sample. To obtained a stratified sample, the population is divided into two or more strata based on common characteristics.
Stratified Sampling
68
Elements are selected from the population at a **uniform interval** that is measured in time, order, or space. There is firstly, a decision on a desired sample size.
Systematic Sampling
69
It is a probability sampling method in which you divide a population into **clusters**, such as districts or schools, and then randomly select some of these clusters as your sample.
Cluster Sampling
70
This is more complex sampling technique which includes
* dividing the population into strata,
* dividing each stratum into clusters, and
* drawing a sample from each cluster using the simple random sampling technique.
Multistage Sampling
71
Basic Types of Non-probability Sampling (4):
1. Accidental Sampling
2. Volunteer Sampling
3. Purposive Sampling
4. Quota Sampling
72
It is a type of nonprobability sampling in which people are sampled simply because they are "convenient" sources of data for researchers. Under this method, researcher does not take special efforts to select the sample, but simply selects those who are immediately available.
Accidental Sampling
73
For this type of sampling, participant **volunteer** rather than being chosen.
Volunteer sampling
74
pertains to having an expert select a representative sample based on his own subjective judgment.
Purposive Sampling
75
sample units are picked for convenience but **certain quotas** (such as the number of persons to interview) are given to interviewers. This design is especially used in market research.
Quota Sampling
76
Large-scale or small-scale.
Size of the sample
77
Where respondents are monitored periodically, cross-section, longitudinal, or quarterly.
Periodicity
78
Descriptive, analytic
Main objective
79
Mail, face-to-face interviews, e-survey,phone survey, or SMS survey.
Methods of data collection
80
Individual, household, establishment, farmer, OFW, etc.
Respondents
81
Ways of Classifying surveys (5)
Size of the sample
Periodicity
Main objective
Methods of data collection
Respondents
82
A type of observational study design.
Cross-sectional study design
83
The investigator measures the outcome and the exposures in the study participants **at the same time.**
Cross-sectional study
84
Researchers **repeatedly examine** the same individuals to detect any changes that might occur over a **period of time**
Longitudinal study
85
Possible sources of biases in a sample surveys that one should be cautious about (4):
Wording of questions
Sensitivity of the survey topic
Interviewer biases
Non-response biases
86
Can influence the response enormously
Wording of questions
87
income, sex, illegal behavior, etc.
Sensitivity of the survey topic
88
Selecting respondents or in the responses generated because of the appearance and demeanor of the interviewer.
Interviewer biases
89
Happens when targeted respondents opt not to provide information in the survey.
Non-response biases
90
Types of survey errors
Sampling Error
Non-sampling Error
91
It results from chance variation from sample to sample in a probability sample.
Sampling Error
92
It is roughly the difference between the value obtained in a sample statistic and the value of the population parameter that would have arisen had a census been conducted. Since estimates of a parameter from probability sample would vary from sample to sample, the variation in estimates serves as a measure of sampling error.
Sampling Error
93
# **Non-sampling Error**
This results if some groups are excluded from the frame and have no chance of being selected.
Coverage error or selection bias
94
# **Non-sampling Error**
________ ____ arising due to weaknesses in question design, respondent error, and interviewer’s impact on the respondent.
Measurement error
94
# **Non-sampling Error**
This occurs when people who do not respond may be different from those who do respond
Non-response error or bias
95
Non-sampling Error (3):
* Coverage error or selection bias
* Non-response error or bias
* Measurement error
