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Statistics > Chp.1 Def. > Flashcards

Chp.1 Def. Flashcards

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1
Q

Statistics

A

is the science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions. In addition, statistics is about providing a measure of confidence in any conclusions.

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2
Q

population

A

the entire group to be studied

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3
Q

individual

A

is a person or object that is a member of the population being studied.

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4
Q

sample

A

is a subset of the population that is being studied

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5
Q

statistic

A

numerical summary of a sample

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6
Q

Descriptive statistics

A
  • consist of organizing and summarizing data.

- Also describes data through numerical summaries, tables, and graphs.

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7
Q

Inferential statistics

A

Uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result.

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8
Q

Parameter

A

numerical summary of a population

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9
Q

Variables

A

characteristics of the individuals within the population .

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10
Q

quantitative variables

A

values of a quantitative variable can be added or subtracted and provide meaningful results.

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11
Q

Nominal level of measurement

A
  • the numbers in the variable are used only to classify the data.
  • In this level of measurement, words, letters, and alpha-numeric symbols can be used.
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12
Q

Qualitative variables

A

allow for classification of individuals based on some attribute or characteristic.

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13
Q

Discrete variable

A

-is a quantitative variable that has either a finite number of possible values or a countable number of possible values.

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14
Q

Countable

A
  • the values result from counting, such as 0,1,2,3 and so on…
  • Discrete variable cannot take on every possible value between any two possible values.
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15
Q

Continuous variable

A
  • is a quantitative variable that has an infinite number of possible values that are not countable.
  • May take on every possible value between any two values.
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16
Q

If you count to get the value of a quantitative variable it is?

A

Discrete

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17
Q

If you measure to get the value of a quantitative variable, it is?

A

Continuous

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18
Q

Data

A

specific values of the variables

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19
Q

Ordinal level of measurement

A
  • depicts some ordered relationship among the variable’s observations.
  • Example: student 1 has a 100 percent on a test (rank1) then the next would be 92 percent 9 (rank 2) then third highest grade was a 81 percent (rank 3rd) and so on…
  • ordering of the measurements.
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20
Q

interval level of measurement

A
  • Classifies and orders the measurements, but also specifies that the distance between each interval on the scale are equivalent along the scale from low interval to high interval.
  • Example: (level of measurement of temperature in centigrade) ===> the distance between 94 degrees C and 96 degrees C is the same as the distance between 100 degrees C and 102 degrees C.
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21
Q

Ratio level of measurement

A

In this level of measurement, the observations, in addition to having equal intervals, can have a value of zero as well.

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22
Q

observational study

A
  • measures the value of the response variable without attempting to influence the value of either the response or explanatory variables.
  • That is, in an observational study, the researcher observes the behavior of the individuals without trying to influence the outcome of the study.
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23
Q

designed experiment

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A

if a researcher assigns the individuals in a study to a certain group, intentionally changes the value of an explanatory variable, and then records the value of the response variable for each group.

24
Q

Confounding

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A

occurs when the effects of two or more explanatory variables are not separated.

25
Lurking variable
An explanatory variable that was not considered in a study, but that affects the value of the response variable in the study.
26
confounding variable
Is an explanatory variable that was considered in a study whose effect cannot be distinguished from a second explanatory variable in the study.
27
what is the big difference between lurking variable and confounding variable?
Lurking variables are not considered in the study.
28
Cross-selectional Studies
Collect information about individuals at a specific point in time or over a very short period of time.
29
Case-control Studies
The studies are retrospective, meaning they require individuals to look back in time or require the researcher to look at existing records
30
Cohort Studies
identifies a group of individuals to participate in the study (the cohort). The cohort is then observed over a long period of time.
31
census
is a list of all individuals in a population along with certain characteristics of each individuals.
32
random Sampling
is the process of using chance to select individuals from a population to be included in the sample
33
simple random sampling
subset of a statistical population in which each member of the subset has an equal probability of being chosen
34
frame
a list of all the individuals within the population
35
sample without replacement
an individual who is selected is removed from the population and cannot be chosen again.
36
sample with placement
a selected individuals is placed back into the population and could be chosen a second time.
37
seed
an initial point for the generator to start creating random numbers
38
stratified sample
- obtained by separating the population into non overlapping groups called strata and then obtaining a simple random sample from each stratum. - The individuals within each stratum should be homogeneous (or similar) in some way.
39
Systematic sample
- obtained by selecting every (k)th individual from the population. - The first individual selected corresponds to a random number between 1 and k.
40
cluster sample
obtained by selecting all individuals within a randomly selected collection or group of individuals.
41
convenience sample
a sample in which the individuals are easily obtained and not based on randomness
42
bias
results of the sample are not representative of the population.
43
sampling bias
the technique used to obtain the sample's individuals tends to favor one part of the population over another.
44
undercoverage
occurs when the proportion of one segment of the population is lower in a sample than it is in the population .
45
Nonresponse Bias
exists when individuals selected to be in the sample who do not respond to the survey have different opinions from those who do not.
46
Response Bias
Exists when the answers on a survey do not reflect the true feelings of the respondent.
47
Nonsampling errors
results from undercoverage, nonresponse bias, response bias, or data-entry error.
48
Sampling error
results from using a sample to estimate information about a population
49
experiment
controlled study conducted to determine the effect varying one or more explanatory variables or factors has on a response variable.
50
treatment
any combination of the values of the factors.
51
single-blind experiments
the experimental unit (or subject) does not know which treatment he or she is receiving.
52
double-blind experiments
neither the experimental unit nor the researcher in contact with the experimental unit knows which treatment the experimental unit is receiving.
53
completely randomized design
is one in which each experimental unit is randomly assigned to a treatment.
54
matched-pairs design
is an experimental design in which the experimental units are paired up.
55
placebo
neutral treatment that has no "real" effect on the dependent variable.

Statistics (4 decks)

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