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Introduction to statistical inference > BIOE > Flashcards

BIOE Flashcards

1
Q

Population, constant regardless of sample/ unkown

A

PARAMETER

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2
Q

Variable, sample

A

STATISTICS

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3
Q

Is the act of paying attention to something in order to gain information

A

OBSERVATION/DESCRIPTIVE

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4
Q

LOGICAL INTERPRETATION OR EXPLANATION OF THE OBSERVATION

A

INFERENCE

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5
Q

USES FIVE SENSES

A

OBSERVATION/DESCRIPTIVE

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6
Q

MENTAL PROCESS

A

INFERENTIAL

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7
Q

IS A CONCLUSION REACHED ON THE BASIS OF EVIDENCE AND REASONING

A

INFERENTIAL

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8
Q

FACILITATE UNDERSTANDING, ANALYSIS, INTERPRETATION OF DATA

A

DESCRIPTIVE

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9
Q

ESTIMATION OF PARAMETERS AND HYPOTHESIS TESTING

A

INFERENTIAL

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10
Q

COMPUTATION OF MEASURES OF CENTRAL TENDENCY AND VARIABILITY. TABULATION AND GRAPHICAL PRESENTATION

A

DESCRIPTIVE

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11
Q

METHODS OF SUMMARIZING AND PRESENTING DATA

A

DESCRIPTIVE

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12
Q 
Process of generalizing
conclusions about the target
population on the basis of
results obtained from a
sample.
A

STATISTICAL INFERENCE

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13
Q

Uses sample statistics to
determine the unknown
parameters of the population

A

STATISTICAL INFERENCE

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14
Q

measures computed using data

from the entire population

A

PARAMETERS

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15
Q

measures computed using data

from the sample

A

STATISTICS

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16
Q

Process by which the statistic computed from a random sample is
used to approximate the corresponding parameter in the population.

A

ESTIMATION

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17
Q

PROCESS OF ESTIMATION

A
  1. GET DATA FROM SAMPLE RESPONDENTS
  2. CALCULATE THE SUMMARY MEASURES (STATISTIC)
  3. USE STATISTIC TO ESTIMATE PARAMETER VALUE
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18
Q

Process of deciding whether or not a hypothesis about the target
population is true based on the sample data.

A

HYPOTHESIS TESTING

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19
Q
  • a statement about the population

- usually something about the value of the parameters

A

HYPOTHESIS

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20
Q

PROCESS OF HYPOTHESIS TESTING

A
  1. GET THE DATA FROM THE SAMPLE
  2. CALCULATE STATISTICS
  3. APPLY STATISTICAL TESTS
  4. DECISION
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21
Q

Frequency distribution of the statistic computed from each of all the
possible samples of the population

A

SAMPLING DISTRIBUTION OF A STATISTIC

22
Q

Knowing the properties of the sampling distribution will help in:

A
  1. ESTIMATING POPULATION PARAMETERS

2. TEST HYPOTHESIS ABOUT POPULATION PARAMETERS

23
Q

TF The sampling distribution of statistical mean reflects the frequency distribution of
sample means of all possible samples of size n.

A

T

24
Q

TF Population parameter is generally known

A

F

25
Q

TF Sampling distribution cannot be constructed in reality

A

T

26
Q

TF The best estimate of the population mean (U) is the mean of the sample mean (x)

A

T

27
Q

Only applicable when the sample is RANDOM

A

POINT ESTIMATE

28
Q

point estimate Identify:
• Variable:
• Population:
• Sample:

A

QUANTITATIVE, PARAMETER WANTED, RANDOM

29
Q

TF statistical mean is an estimate of population mean and they are equal

A

F

30
Q

Interval constructed is called:

A

CONFIDENCE LEVEL

31
Q
  • from literature

- from previous studies

A

POPULATION STANDARD DEVIATION Z TEST

32
Q

IF POPULATION SD IS ABSENT WE WILL USE?

A

STATISCAL SD T TEST

33
Q

Variable of interest of population proportion is

A

QUALITATIVE

34
Q

TF In sampling distribution of population propotions, The sampling distribution of p reflects the frequency distribution of
population proportions of all possible samples of size n

A

F- POPULATION - T- SAMPLE

35
Q

TF The distribution is normally distributed in sampling distribution of population proportion.

A

T

36
Q

decision is towards

A

null hypothesis

37
Q

is towards alternative hypothesis

A

conclusion

38
Q

• A non-parametric test that test the association between two
variables.

A

CHI-SQUARE TEST OF INDEPENDENCE

38
Q

• A parametric test used in determining relationship between

two set of data.

A

Pearson r (Bivariate - 2 variables)

39
Q

A non-parametric test used to find out if there is a significant
relationship between 2 variables.

A

Spearman rank (rs)

40
Q
  • The joint distribution of the variables x and y is also a normal distribution
A

Pearson r (Bivariate - 2 variables)

41
Q

Under correlation analysis

A 
Spearman rank (rs)
Pearson r (Bivariate - 2 variables)
42
Q

• Qualitative Description of Coefficient of Correlation

A

Pearson r (bivariate - 2 variables)

43
Q

– used to measure both the strength
and the direction of the relationship between two quantitative variable. Done through the computation of the correlation
coefficient.

A

Correlation analysis

44
Q

used coefficient in interval/ratio

A

pearson r

45
Q

used coefficient for ordinal data

A

spearman rank

46
Q

TF in pearson r, the closer the value to one, the greater the strength of linear relationship

A

T

47
Q

The value in pearson r indicates?

A

magnitude

48
Q
  • we will test for the existence of relationship or association between two qualitative variables in a single population.
A

CHI-SQUARE TEST OF INDEPENDENCE

49
Q

We will we will test whether or not variable x is associated with variable y

A

CHI-SQUARE TEST OF INDEPENCE

Introduction to statistical inference (2 decks)

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