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Statistics > exam 2 > Flashcards

exam 2 Flashcards

1
Q

Why do we have reliability and variability?

A

In order to ensure that data collected IS WHAT WE THINK THER ARE, or what we use to measure IS IN FACT MEASUING DATA.
because INTERPRETATION OF DATA HAS CONSEQUENCES & All statistics IS MEANINGLESS unless we are confident that we know what we are looking at

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2
Q

What is a measurement scale?

A

The assignment of values to outcomes following a set of rules. PARTICULAR LEVELS AT WHICH OUTCOMES ARE BEING MEASURED.

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3
Q

What are the 4 different types of measurement scale?

A

nominal, ordinal, interval and ratio, always DEGREE OF ERROR, different PRECISENESS

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4
Q

Definition+example of a nominal mesurement scale

A

“names” (nominal- Latin). It is the LEAST PRECISE. DATA CAN ONLY BE CLASSIFIED.
MUTUALLY EXCLUSIVE CATEGORIES, outcome FIT IN ONE AND ONLY ONE.
Ex: Gender, Ethnicity, political affiliation

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5
Q

Definition+example of an ordinal mesurement scale

A

ORDER and the things being measured are ordered. DATA ARE RANKED Ex: your rank in class…. (We know that #1 is better than #2, but we don’t know by how much)

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6
Q

Definition+example of an interval mesurement scale

A

: MEANINGFUL DIFFERENCE BETWEEN VALUES. tool based on A CONTINUUM. Ex:temperature, dress size, metrics?

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7
Q

Definition+example of a ratio mesurement scale

A

MEANINGFUL 0 POINT & RATIO between VALUES.
EX: Number of boys versus 0 degrees
0 boys would be the ABSOLUTE VALUE thus the RATIO, since there are actually no boys present in the room

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8
Q

What are the 4 general scales rules?

A
  • Any outcome can be assigned to one of 4 scales of measurement.
  • ORDER FROM LEAST TO MOST PRECISE ( nominal-ratio)
  • HIGHER SCALE ARE MORE INFORMATIVE AND PRECISE
  • THE MORE PRECISE, contains ALL qualities of scale BELOW
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9
Q

What is reliability?

A

test used as a measurement tool is measuring something CONSISTENTLY. we should be able to use the test TIME after TIME and get SIMILAR RESULTS.

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10
Q

What are the two test score element;

A

*observed score (score obtained i.e. 94.5% in my stats first exam) versus
* true score (97%)
Observed score= true score+ error score (reason why test score vary from being 100% true)

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11
Q

what is the first form of reliability? example

A

1)TEST-RETEST: examine if test is reliable over TIME, helps examine changes over time.
if conditions are the same, results should be the same.
ex: same exam taken different results each time its taken=not reliable

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12
Q

What is the third form of reliability? example

A

3)Internal CONSISTENCY: extent to which a test or procedure is CONSISTENT WITHIN ITSELF i.e., questionnaire items or questions in an interview should all be measuring the same thing= REPRESENT ONE dimension or area of interest CRONBACH’S ALPHA

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13
Q

To remember on Reliability

A

Ensure instructions are standardized and clear across all settings

  • Increase no of observations to increase the chance of the sample being reliable.
  • Delete all unclear items.
  • Moderate the easiness/difficulty of test
  • Minimize external effects
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14
Q

What is validity?

A

The tool MEASURES WHAT IT SAYS IT DOES; what it’s supposed to

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15
Q

What is the first type of validity?

A

CONTENT VALIDITY:Good SAMPLE of the specific “UNIVERSE”

ex: Does the content of a test cover everything in the area of interest?

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16
Q

What is the second type of validity?

A

CRITERION VALIDITY:Systematically RELATED TO OTHER CRITERION
1 Concurrent: New measure test scores are CORRELATED with those FROM AN ESTABLISHED VALID test
ex: we have a high positive correlation between scores on the new and old tests. this test valid!

2 Predictive:futur
Ex:Can an intelligence test at age 3 predict academic performance at 21?

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17
Q

Not finding the validity evidence

A

means that your test is not doing what it should.

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18
Q

when no criterion validity

A

to re-examine the nature of the items on the test and answer questions the way you expect the responses to be.

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19
Q

Not finding construct validity

A

means that you have to take a closer look at the theoretical rationale that underlies the test you have developed.

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20
Q

Relationship between validity and reliability

A

A test can be reliable and not valid, but not the other way around. Because a test can do what it does over and over, but still not do what it is supposed to do.

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21
Q

HYPOTHESIS

Definition

A

It is an EDUCATED GUESS
The “QUESTION/PROBLEM STATEMENT” we want to answer/address with research
TRANSLATES A PROBLEM IN A QUESTION that can be tested.
,

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22
Q

How to formulate a good hypothesis

A
  • should TRANSLATE A statement/research question into a more amenable testing form.
  • Use the RESEARCH question as a GUIDE. Then the hypothesis will determine the techniques to use to create a good hypothesis
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23
Q

rules about Samples and population

A

Samples should ACCURATELY, to allow a higher a degree of GENERALIZATION for the study results.

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24
Q

Null Hypothesis def:

A

Statement that two or more things are EQUAL OR UNRELATED to each other
H0 : m1 = m2 or H0 : rm1m2 = 0

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25
Q

Purpose of the NH

A

The NH acts as BENCHMARK & STARTING POINT against which the actual OUTCOMES of a study can be MEASURED (STATE OF AFFAIR accepted coz no other info)

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26
Q

Research hypothesis def

A

STATEMENT OF INEQUALITY posits that there is a RELATIONSHIP between variables.

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27
Q

RH two forms

A

•NON-DIRECTIONAL RH (ONE TAIL): UNSPECIFIED DIFFERENCE between groups, H1 : X1 > X2 more than/less than
• DIRECTIONAL RH (2 TAILS): SPECIFIED DIFFERENCE between groups.
H1 : X1 ≠ X2

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28
Q

Purpose of RH

A

DIRECTLY TESTED in RESEARCH. results compared with you expect by CHANCE ALONE & see what is a more attractive explanation for any differences observed between groups.

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29
Q

Difference between the NH and the RH

A

•RELATIONSHIP (NH-YES & RH- NO)
•NH -POPULATION &the RH -SAMPLE.
•NH INDIRECTLY tested & RH DIRECTLY ested
•NH in GREEK symbols & RH in ROMAN symbols.
*NH is IMPLIED, & RH is EXPLICIT- reason why NH is not used in research reports.

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30
Q

What makes a good hypothesis?

A 
•DECLARATIVE form & NOT A QUESTION
•POSITS A RELATIONSHIP between VARIABLES variables
•REFLECT THEORYon which based
•Should be BRIEF & TO THE POINT.
-TESTABLE (unambiguous)
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31
Q

PROBALITY

Why?

A

*BASIS for the NORMAL CURVE & the FOUNDATION for INFERENTIAL statistics.
• determining the degree of confidence we have in stating that a statement is true.DIDNT HAPPEN BY CHANCE

32
Q

Probility: normal curve (bell-shaped curve)
def:

A

it is a VISUAL REPRESENTATION of a distribution of scores

33
Q

what are the probability normal curve 3 characteristics?

A
  • NOT SKEWED (mean=median=mode)
  • SYMETRICAL-both HALVES r IDENTICAL.
  • ASYMPTOTIC: as they come CLOSER to HORIZONTAL AXIS, they NEVER TOUCH.
34
Q

explain the reasons for the curve characteristics?

A

With large sets of data, & repeated samples of data from population, the VALUE IN CURVE APPROXIMATE THE SHAPE of a normal curve. EVENTS in the EXTREME tend to have a SMALLER PROBABILITY , and event in the MIDDLE have a HIGHER probability.

35
Q

Probability

standard scores def:

A

scores that COMPARABLE because they are STANDARDIZED, allow us to COMPARE scores with DIFFERENT MEANS
They help decide THE PROBABILITY OF SOME EVENT OCCURING
LIKELY, MORE LIKELY, LESS LIKELY

36
Q

Probability

What do z scores represent?

A

RAW SCORES & a particular LOCATION on the x-axis

-the LARGER the Z score, the further awya from the mean

37
Q

Hypothesis testing and z scores

A

*NH - no difference between groups with a chance of a 100% of that occurring.
*RH shows that the likelihood of that event occurring is somewhat extreme;
RH - better explanation than NH.
*Z score will show the LIKEHOOD OF EVENT HAPPENING

38
Q

Inferential statistics: significant

A

any DIFFERENCE between GROUPS is caused by an EXTERNAL FACTORS & not by CHANCEalone.
allowing leeway on fact that difference in groups could be may be caused by uncontrollable factors.

39
Q

Inferential Stats: what is Significance level?

A

is the DEGREE WE ALLOW FOR ERROR, the level of chance or risk we are willing to take that the RESULTS in an experiment are NOT DUE TO CHANCE ALONE.

40
Q

What is the difference between significance and meaningfulness?

A

Significance(PROBABILITY) is not meaningful(CONTEXT) on its own (variability, difference of people, mean difference): it is influenced by the mean of the groups, variability and the difference in groups

41
Q

Define inferential statistics

A

Tool used to infer result from sample to population

42
Q

How does inference work?

A
  • sample
  • test
  • significance
  • inference
43
Q

Steps for significance

A
  • NH
  • .01or .05
  • Compute T
  • compare T to Bar
  • reject/accept NH
44
Q

What is confidence interval?

A

The BEST ESTIMATE OF THE RANGE of population in a sample

45
Q

What do we need Z test for?

A

To compare a SAMPLE MEAN to a POPULATION MEAN

46
Q

Tea

A

Tool look up MEAN DIFFERENCES between of 1 or MORE VARIABLE between GROUPS that are INDEPENDENT of 1 ANOTHER (independents/dependents samples)

47
Q

When to use tea?

A

With independent and/or dependent samples

48
Q

Assumptions of T

A

Observations are INDEPENDENT
2 populations must be NORMAL
2 groups with EQUAL VARIANCE

49
Q

Explain

t(58)=-.14>.05

A

t = test statistics
58 =degree of freedom
-.14 = obtained value
P>.05 =probability

50
Q

What is degree of freedom?

A

EVERYTHING u need to KNOW before u KNOW the TEST
Number of entities that are FREE TO VARY
Df = n1-1+n2-1 in independent T2
Df=n-1 in dependent T1

51
Q

Explain tails

A
  • 2 tails= NON-DIRECTIONAL RH, results could go either way

* 1 tail= DIRECTIONAL RH, results could only go one way

52
Q

What are effects size?

A 
HOW BIG IS BIG? How different is different- magnitude 
Small 0.0-2.0 how similar r gps/overlap 
Medium 2.0-.50
Large .5 and above
(Xbar1-Xbar2)/SD from either gp
53
Q

SPSS T

A

Analyze, compare means, independents samples T-test/paired samples T test

54
Q

Z scores observation

A

Scores below mean r negative
Positive scores r right to the mean
Z scores r comparable

55
Q

Z scores formula

A

Z= x-x
—
Sd

56
Q

what is the second form of reliability? example

A

2) PARRALEL FORM:To examine the EQUIVALENCE OR SIMILAR FORM of the same test.
ex: Two versions of the same test should yield equivalent results =not reliable

57
Q

what is the fourth form of reliability?

A

4)Interrater reliability: HOW MUCH 2 REATERS AGREE on their judgments and if they follow the same procedures.=use STANDARDISE CATEGORIES
There SHOULD BE A HIGH POSITIVE CORRELATION between the scores of different observers

58
Q

Chronbach’s Aplha

A

special measure of reliability INTERNAL CONSISTENCY:how closely related a set of items are as a group. The more consistently an item vary with the total score on the test, the higher the Chronbach’s Aplha value. (as the intercorrelations among test items increase)
People who do well should do well on harder questions

59
Q

if you can establish validity

A
  • lower the error
  • use standardised instructions
  • increase no of observation
  • delete unclear items
  • moderate the test
  • eliminate external event
60
Q

What is the importance of validity?

A

Often times we CAN’T “SEE” the CONCEPT we are measuring, i.e. “intelligence,” or “depression” – therefore establishing validity is important

61
Q

what is internal validity

A

The tool is measuring WHAT IT IS INTENDING to measure

62
Q

what is external validity

A

The findings can be GENERALIZED BEYOND THE CONTEXT of the research situation

63
Q

What is the third type of validity?

A

CONSTRUCT VALIDITY: Related to an UNDERLYING IDEA

Ex: social status

64
Q

Z-scores and SD

A

when comparing scores across distribution, Z scores and SD are EQUIVALENT

65
Q

percentages in the curve

A

34,13; 15,59; 2,15;0,13

66
Q

What is hypothesis testing?

A

procedure that DECIDES that the OUTCOME of a STUDY supports a THEORY at a POPULATION level

67
Q

error type 1

A

rejecting a TRUE hypothesis. Claiming a difference when there is NO DIFERENCE
FALSE POSITIVE
greek alpha

68
Q

error type 2

A

accepting a FALSE hypothesis.Claiming there is no difference while THERE IS A DIFFERENCE.
FALSE NEGATIVE
greek beta

69
Q

p ≤ .05

A

On any one test of the NH there is a 5% chance you will reject it when the NH is actually true.
The probability of observing this outcome in the “normal population” is less than .05. (the “Outcome” is rejecting the NH when it is true)
There is a 5% probability that a score is that extreme if theNH is true

70
Q

balancing errors

A

If you set your significance level at .000001 to control for a Type I error, you risk being too stringent to detect a real effect – committing a Type II error.
Tradeoffs must be made

71
Q

SIGNIFICANT

A

If p<.05 that means it is SIGNIFICANT.

If obtained value is MORE extreme, REJECT NH

72
Q

NOT SIGNIFICANT

A

p>.05 means a result is not significant

If obtained value is NOT MORE extreme, ACCEPT NH

73
Q

what is a Test Statistic (Obtained Value)

A

– RESULT of a specific STATISTICAL TEST done on a sample

74
Q

independent samples

A

SEPARATE groups TESTED ONCE (males vs.females)
only 2 groups total
interested in DIFFERENCE BETWEEN GROUPS

75
Q

NUMERATOR IN T STATISTIC

A

DIFFERENCE BETWEEN MEANS

76
Q

Denominator in T Statistics

A

AMOUNT of VARIANCE WITHIN & BETWEEN groups

Statistics (9 decks)

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