BSLEC 1 Flashcards

1
Q

Set of mathematical procedures for organizing, summarizing, and interpreting information

A

Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

some of the most fundamental tools and techniques of the scientific method:

A

forming hypotheses.
designing experiments and observational studies,
gathering data,
summarizing data,
drawing inferences from data (e.g., testing hypotheses)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

refers to a numerical quantity computed from sample data (e.g., the mean, the median, the maximum)

A

statistic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

study and development of statistical theory and methods in the abstract

A

Mathematical Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

application of statistical methods to solve real problems involving randomly generated data, and the development of new statistical methodology motivated by real problems

A

Applied Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

branch of applied statistics directed toward applications in the health sciences and biology

A

Biostatistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

the set of all measurements of interest to a researcher.

A

Population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Populations can be thought of as ___

A

existing or conceptual.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

well-defined sets of data containing elements that could be identified explicitly

A

Existing populations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

are non-existing, yet visualized, or imaginable, sets of measurements.

A

Conceptual populations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Set of individuals selected from a population, usually intended to represent the population in a research study

A

Sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

A value, usually numerical value, that describes a population

A

Parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

A value, usually a numerical value, that

describes a sample

A

Statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Usually derived from measurements of the individuals in the population

A

Parameter

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

A sample statistic is ____ of the average of the statistic is equal to the population parameter.

A

unbiased

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

A sample statistic is ___ if the average value of the statistic either underestimates or overestimates the corresponding population parameter.

A

biased

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Two types of variables

A

Qualitative variables

Quantitative variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

can assume numeric values

A

Quantitative variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Nonnumeric in nature

A

Qualitative variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Quantitative variables

are classified into two groups:

A

discrete variables and continuous variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Variable having only Integer values

A

Discrete variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

variable that is not restricted to particular values

A

Continuous variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Observations (I.e., dependent variables) that occur in one of two possible states, often labelled zero and one.

A

Binary variable

24
Q

Usually an independent or predictor variable that contains values indicating membership in one of several possible categories

A

Categorical Variable

25
A variable that obscures the effects of another variable.
Confounding variable
26
An extraneous variable that an investigator does not wish to examine in a study.
Control variable
27
The presumed effect in a nonexperimental study.
Criterion variable
28
The presumed effect in an experimental study.
Dependent variable
29
Created by recoding categorical variables that have more than two categories into a series of binary variables,
Dummy Variables
30
A variable that is an inherent part of the system being studied and that is determined from within the system.
Endogenous variable
31
A variable entering from and determined from outside of the system being studied
Exogenous variable
32
The presumed cause in an experimental study. All other variables that may impact the andent dependent variable are controlled.
Independent variable
33
A variable that explains a relation or provides a causal link between other variables.
Intervening variable .
34
lso called by some authors "mediating variable" or "Intermediary variable."
Intervening variable .
35
An underlying variable that cannot be observed.
Latent variable
36
An observed variable assumed to indicate the presence of a latent variable.
Manifest variable
37
Also known as an Indicator variable.
Manifest variable
38
Synonym for intervening variable.
Mediating variable
39
A variable that influences, or moderates, the relation between two other variables and thus produces an interaction effect.
Moderating variable
40
A variable used to rank a sample of individuals with respect to some characteristics, but differences (.e., Intervals) and different points of the scale are not necessarily equivalent.
Ordinal variable
41
The presumed effect in a nonexperimental study. Synonym for criterion variable,
Outcome variable
42
Variables that can have more than two possible values, Strictly speaking, this includes all but binary variables.
Polychotomous variables
43
The presumed "cause" of a nonexperimental study. Often used in correlational studies.
Predictor variable
44
Measurements or observations
Data
45
A collection of measurements or observations
Data set
46
A single measurement or observation and is commonly called a score or raw score.
Datum
47
Firsthand data or raw data
PRIMARY DATA
48
which is already collected and recorded by any person other than the user for a purpose, not relating to the current research problem
Second-hand information
49
readily available form of data collected from various sources like censuses, government publications, internal records of the organization, reports, books, journal articles, websites, etc.
SECONDARY DATA
50
Two Types of Statistical Method
Descriptive statistics | Inferential statistics
51
Concerned with the describing the target population
Descriptive Statistics
52
Make inferences from the sample and generalize them to the population.
Inferential Statistics
53
Compares,tests and predicts future outcomes.
Inferential Statistics
54
Organize,analyze and present the data in a meaningful manner
Descriptive Statistics
55
Final results are shown in form of charts, tables and graph
Descriptive Statistics
56
Final result is the probability scores
Inferential Statistics