Strategy & Math Flashcards Preview

Question 1

Q

cos 0 30 45 60 90

A

Question 2

Q

sin 0 30 45 60 90

A

1

Question 3

Q

SI units:
- Femto
- Kilo
- Deci

Answer

A

Femto

10^-15

Kilo

10³

Deci

10^-1

Question 4

Q

SI Units:

Mega
Pico
Hecto

Answer

A

10⁶

10^-12

10²

Question 5

Q

SI Units:

Tera
Nano
Centi

Answer

A

10¹²

10^-9

10^-2

Question 6

Q

SI Units:

Deca
Giga
Micro
Milli

Answer

A

10¹

10⁹

10^-6

10^-3

Question 7

Q

Convert 650 nm to SI units

Answer

A

650 x 10⁹

Question 8

Q

Const. force (not velocity!) causes WHAT acceleration?

Answer

A

constant acceleration

Question 9

Q

When you throw a baseball, when is the only time it is accelerating?

Answer

A

Only when it is in contact with your hand

Question 10

Q

Increasing something by 25% is the same as multiplying it by what?

Answer

A

x 5/4

Question 11

Q

Define “mass”

Answer

A

the measure of an object’s inertia

Question 12

Q

Define “inertia”

Answer

A

the ability of an object to RESIST its change in velocity

Question 13

Q

Where on a mass/object is its “Center of Gravity?”

Answer

A

is at the center of the mass/object

Question 14

Q

Where is the “Center of buoyancy?”

Answer

A

at center of mass of the FLUID displaced by the submerged object

Question 15

Q

Scalar or Vector?

Mass

A

scalar

Question 16

Q

Scalar or Vector?

temperature

A

scalar

Question 17

Q

Scalar or Vector?

velocity

A

vector

Question 18

Q

Scalar or Vector?

speed

A

scalar

Question 19

Q

Scalar or Vector?

displacement

A

vector

Question 20

Q

Scalar or Vector?

acceleration

A

vector

Question 21

Q

Scalar or Vector?

force

A

vector

Question 22

Q

Scalar or Vector?

work

A

scalar

Question 23

Q

Scalar or Vector?

energy

A

scalar

Question 24

Q

Scalar or Vector?

weight

A

vector

Question 25

Q

Scalar or Vector?

charge

A

scalar

Question 26

Q

Scalar or Vector?

electric field

A

vector

Question 27

Q

Scalar or Vector?

magnetic field, B

A

vector

Question 28

Q

Scalar or Vector?

time

A

scalar

Question 29

Q

Scalar or Vector?

momentum

A

vector

Question 30

Q

Scalar or Vector?

impulse

A

vector

Question 31

Q

Scalar or Vector?

density

A

scalar

Question 32

Q

Scalar or Vector?

torque

A

vector

Question 33

Q

What are the 4 questions that test conceptual understanding?

Answer

A

Can I visualize it?
Can I draw a picture/graph/diagram of it?
Can i explain it to someone in layman’s terms?
Can i think of and describe real-life examples?

Question 34

Q

Area of triangle
- formula=?

Answer

A

A_tri=1/2 bh

Question 35

Q

Vol of sphere formula

Answer

A

V_sphere=4/3 πr³

Question 36

Q

SA of sphere formula

A

4pir^2

Question 37

Q

Manipulating equations mnemonics

Answer

A

SSISDDODIOSD

Question 38

Q

sqrt 2=

A

1.4

Question 39

Q

sqrt 3=

A

1.7

Question 40

Q

sqrt 2/2=

A

.7

Question 41

Q

sqrt 3/2=

A

.9

Question 42

Q

product of [H][OH] always equals:

A

1x10^-14

Question 43

Q

Doppler effect formula

Answer

A

deltaf/fs=v/c

Question 44

Q

Be careful of S.N.E.W.L

Answer

A

Qualifiers (Write these down!) “StrengthensNot ExceptWeakensLeast”

Question 45

Q

tan0=

Answer

A

sin0/cos0

Question 46

Q

sin^2x+cos^2x=

A

1

Question 47

Q

11^2

A

121

Question 48

Q

12^2

A

144

Question 49

Q

13^2

A

169

Question 50

Q

14^2

A

196

Question 51

Q

15^2

A

225

Question 52

Q

Multiplying 2 vectors: If answer is scalar, (ie work), also mult by what?

A

cos0

Question 53

Q

multiplying 2 vectors: if answer is a 3rd vector (ie torque), also multiply by what?

Answer

A

sin0T=Frsin0

Question 54

Q

Decimal equivalent:1/5

A

.2

Question 55

Q

Decimal equivalent:1/8

A

.125

Question 56

Q

Decimal equivalent:1/9

A

.11

Question 57

Q

For fractions where numerator is higher (like 13/5), what should you do to solve?

Answer

A

Create compound fraction: 5x2=10, left w/ 3/5 13/5 becomes 2x (3/5)

Question 58

Q

For fractions where denominator is larger, what should you do to solve?

Answer

A

“High/Low” methodChange denominator to 1 digit higher or 1 digit lowerex:3/7 changed to 3/6 and 3/8. Must be a little less than .5

Question 59

Q

When multiplying with scientific notation, what happens to the exponents?

Answer

A

You add them together

Question 60

Q

When dividing with scientific notation, what do you do with the exponents?

Answer

A

You subtract them

Question 61

Q

Estimating Fractions

29/4 =?

Answer

A

=7.25

4 x 7=28

¼ is left behind

Question 62

Q

Estimating Square Roots
- “High/Low” Method

What is the square root of 72?

Answer

A

√81=9
√64=8

∴ the square root of 72 is somewhere in between, so about 8.5

Question 63

Q

Surface Area of a Sphere
- Formula=?

Answer

A

SA_sphere= 4πr²

Question 64

Q

Trigonometry
- All of the angles in any triangle must add up to?

A

180°

Answer 28

A

sinθ=Opp/Hyp

cosθ=Adj/Hyp

tanθ=Opp/Adj

”SOHCAHTOA”

Answer 29

A

π radians=180°
2π radians=360°

There are approximately 6 radians in ONE CIRCLE

∴, if something is rotating at 12 rad/sec, it is making 2 revolutions/ sec

Answer 30

A

sin^-1
- cosecant
cos^-1
- secant
tan^-1
- cotangent

Answer 31

A

tanθ=sinθ / cosθ

Answer 32

A

X=½at²

NON-linear
Linear
NON-linear

Answer 33

A

The log of an exponential function becomes linear, so exponential functions graphed on semi-log axes end up being linear

…AND a linear function would be non-linear

If the exponential function is graphed on log-log axes, the function will be non-linear

The table below may be helpful*
The semilog graph described is for a linear X-axis and a logarithmic Y-axis (log-lin type not lin-log)

Answer 34

A

A semi-log graph has a logarithmic scale on one axis, but a linear scale on the other axis

Answer 35

A

A log-log graph has a logarithmic scale on BOTH axes

Answer 36

A

inversely

Answer 37

A

inversely

Answer 38

A

x∝t²

If the distance traveled (x) increases by a factor of three (3), then time must increase by some factor that, when squared, will also equal a factor of three
This number is the square root of three, so time will increase by a factor of 1.7—*
or be 1.7 TIMES larger than it was originally*

Answer 39

A

a Testable hypothesis

basically, it can be used to verify a clear YES or NO answer

Answer 40

A

Experimental or “Basic Science” Research

Laboratory research conducted in a highly controlled environment;
- NOT on human subjects!
This type of research allows investigators to have the strictest level of control over all possible variables and conditions
- Experimental research is therefore thought to be the most reliable way to indicate CAUSATION

Answer 41

A

Human Subjects Research

2 Types: Experimental & Observational

Research conducted outside the laboratory, often on human subjects
Drug trials are a common and familiar example
Has less control over conditions than in “Basic Science” research*
making conclusions less definitive*
For example, a study drug may fail to show decreased blood pressure in some subjects
- However, it is later discovered that all participants did not follow the strict low-sodium diet required by the study guidelines
  - This was thought to influence blood pressure measurements in those patients

Answer 42

A

Research involves a specific intervention controlled by the investigator
Subjects are separated into control and treatment groups.
- e.g., To test the efficacy of a new drug, patients with allergies are separated into groups randomly and given either the drug (treatment) or placebo (control)

Answer 43

A

Investigator observes data WITHOUT:
- Direct control over the variables, OR
- Implementation of interventions

Example:

An investigator reviews case studies from COPD [chronic obstructive pulmonary disease] patients and examines demographic information and lifestyle choices in an attempt to identify risk factors associated with COPD)

Answer 44

A

DO GOOD.

Doctors and researchers have an obligation to promote the welfare of patients or study participants
Patient welfare should always be a primary consideration in study design and execution

ENDING A STUDY BECAUSE OF POSITIVE (“GOOD”) RESULTS:

One classical application of beneficence in human subjects research is the obligation to END an experimental study when it is clear a drug or intervention results in obvious benefit
This may sound counterintuitive, but remember that each study must have control groups
If a drug is found to save the lives of dying cancer patients…..
- it is NOT ethical to continue the study long-term and thereby save the lives of those in the treatment groups
- …while those in the control groups are withheld from taking a drug researchers know could help them

Answer 45

A

DO NO HARM

This is the physician’s oath, but applies equally to researchers
Doctors and researchers have an obligation to not harm their patients or study participants

ENDING A STUDY BECAUSE OF NEGATIVE (“BAD”) RESULTS:

Researchers are similarly obligated to end a research study as soon as it is verified that a treatment harms the subjects
Most early research that is criticized today is drawn into question because it violated this principle
The famous psychology study involving “Little Albert,” for example, while revealing evidence about conditioning, is now thought to have had an unethical impact on the young child involved :(
- Albert was conditioned to have severe generalized phobias of animals and the study involved obvious emotional trauma to Albert.

Answer 46

A

Patient autonomy and informed consent

Physicians and researchers have an obligation to:
- Inform patients or study participants, and
- Allow them to make decisions about their own health and treatment

At times, some deception (e.g., placebo) is necessary to effect research

However, this should be the minimal amount possible, the truth should be revealed as soon as possible, and deception in general should be approved by an Internal Review Board (IRB)

Answer 47

A

Equal treatment of all people

Equal allocation of resources, to the extent possible
- ..without bias, prejudice or discrimination.

Answer 48

A

Cohort Study

is a longitudinal study observing characteristics (usually risk factors) of members of a cohort across time

Cohort studies usually employ correlations to demonstrate a relationship

EXAMPLES:

Smokers (Cohort A) were three times more likely to develop lung cancer before the age of 50 than non-smokers (Cohort B)
A statistically significant correlation (r = 0.84, p < 0.01) exists between socioeconomic status and frequency of pre-term births

Notice that this is NOT the manipulation of an independent variable, THEN observing outcomes

Scientists are simply observing data about people or populations as it exists and looking for relationships

Answer 49

A

Cross-Sectional study

is the analysis of data collected from a population or sample AT ONE SPECIFIC TIME
- …compared to across a time period for cohort studies

EXAMPLES:

A survey of the U.S. population to determine the current prevalence of a disease
A study examines blood pressure among those with incomes above $100K/year and those below $100K.

Answer 50

A

Case-Control Study

By design, a Case-Control Study is always RETROSPECTIVE

Is an observational study of individuals in the population WITH a condition present
- …and comparison of that group to a control group of persons WITHOUT the disease IN THAT SAME POPULATION (i.e., “reference group”)

Most famous Case-Control Study is the one is the study that linked lung cancer to smoking

EXAMPLE:

There is a suspicion that zinc oxide (the white non-absorbent sunscreen traditionally worn by lifeguards) is more effective at preventing sunburns that lead to skin cancer than absorbent sunscreen lotions
A case-control study was conducted to investigate if exposure to zinc oxide is a more effective skin cancer prevention measure
The study involved comparing a group of former lifeguards that HAD developed cancer on their cheeks and noses (cases) to a group of lifeguards (same population) WITHOUT this type of cancer (controls)
- …and assess their prior exposure to:
  - zinc oxide OR
  - absorbent sunscreen lotions
This study would be retrospective in that the former lifeguards would be asked to recall (“Recall Bias”) which type of sunscreen they used on their face and approximately how often

Answer 51

A

Useful for RARE outcomes

Answer 52

A

INDEPENDENT VARIABLE

The variable that gets:
- MANIPULATED (or rather…)

changed BY THE INVESTIGATOR!!

Also called the “predictor variable.”

It can be thought of as the “CAUSE”

Always goes on the X-axis

DEPENDENT VARIABLE

The variable MEASURED
- ….as a response to changes in the INdependent variable
Also called the “outcome variable”

It can be thought of as the “EFFECT”

You can’t “Add” a Dependent Variable
- i.e., you can “add” an outcome…you can only “add” something that will change the outcome
Always goes on the Y-axis

Answer 53

A

Independent: Time Spent studying
- Dependent: Test score
Independent: Octane rating of gas
- Dependent: Gas mileage
Independent: Dosage of medication
- Dependent: Survival Rate
Independent: Exposure to violent VG’s
- Dependent: Lvl of aggression

Answer 54

A

Control Group

A group or trial in which ALL conditions and environmental factors are IDENTICAL to the treatment group–

EXCEPT for the treatment itself!!

Answer 55

A

POSITIVE control

Is a group given a treatment with a KNOWN OUTCOME

PURPOSE:

The positive control can be compared to the unknown outcome of whatever treatment is being studied

EXAMPLE:

If your experiment results in the ability of bacteria to grow on a petri plate containing antibiotic, your positive control will be bacteria that are known to carry the appropriate drug resistance marker

Even if none of your experimental bacteria grow, as long as there is growth of the positive control

….you know that growth was at least POSSIBLE

Answer 56

A

NEGATIVE control

is a group that does NOT receive any condition or treatment
- …and for which NO outcome is expected

PURPOSE:

To help expose CONFOUNDING variables

EXAMPLE:

An experiment results in the ability of bacteria to grow on a petri plate containing antibiotic

NEGATIVE Control:

Bacteria which do NOT carry a drug resistance marker should NOT be able to grow on a petri plate containing antibiotic

∴ if growth IS observed, it is a red flag that something is WRONG with the experiment!

“What could be one reason for growth?”
- aka what could be a confounding variable here?

Answer 57

A

Selection Bias

The method used to select participants is

NOT TRULY RANDOM

∴
- the results are not representative of the whole population
- There are “systematic BASELINE differences” among participants

….because true randomization was not achieved

Answer 58

A

SPECIFIC REAL AREA BIAS:

is bias introduced by conducting the study in a specific area that does NOT include a representative sampling of the population being studied

For example:

A study of U.S. eating habits (population= U.S. citizens) conducted at the gym leaves out all those who do not attend the gym—particularly bad because:
- being a member of a gym is likely to confound with eating habits

Having a specific location for a study does NOT always mean “specific real area bias” will exist!

For example:

a study investigating the drug-using habits of Maricopa County High School students (population=HS students) would not be biased if conducted only at the high school
- because the sample would be representative of the population

Answer 59

A

Self-Selection bias

is bias introduced when participants in the study have the ability to:
- choose to participate or not to participate, OR ,
- to determine their level of involvement

Surveys show significant self-selection bias

For example:

Feedback boxes at fast-food establishments are far from representative of customer opinions
- Generally because those with negative opinions have been shown to be far more likely to fill out such surveys
  - (as opposed to those with positive experiences)

Answer 60

A

Pre-Screening or Advertising Bias:

Occurs when the screening or advertising *PROCESS* *ITSELF* results in
- …an unrepresentative sample

For example:

Advertisements asking for volunteers FOR THE SAME STUDY that are worded:
- “Volunteers needed for an obesity study”

OR

“Volunteers needed for a weightloss study”

…will likely elicit different volunteers

(Obesity=BAD! Weightloss=GOOD!)

Answer 61

A

Exclusion Bias

Refers to the exclusion of an entire group from the population

Example:

A study about childhood education that does not survey any homeschooled children

Answer 62

A

Healthy User Bias

When the persons included in the study are likely to be healthier
- ….than the general population

Example:

Studying cardiac atherosclerosis among participants in a triathalon

Answer 63

A

Berkson’s Fallacy

Is the selection of participants from hospitals–
- where the participants are likely to be LESS healthy than the general population

Is the OPPOSITE EFFECT of the Healthy-User Bias

Answer 64

A

OVERmatching

Matching on variables other than those that are risk factors for the disease under study

Is a negative outcome resulting from what is normally a good practice:
matching for potentially confounding variables*
i.e., age-matched

EXAMPLE:

If you use neighborhood controls in a study on NUTRITION and TUBERCULOSIS…
You are inadvertedly matching for SES (and thus, nutrition)*

Answer 65

A

OBSERVER BIAS:

Observers (or researchers) KNOW THE GOALS of the study or the hypotheses

…and allow this knowledge to INFLUENCE their observations during the study

Foot Study Example:

We want statistically significant data, so we “observe” things in a way that will help us get statistically significant data

Answer 66

A

Demand Characteristics

PARTICIPANTS form an interpretation of the experiment’s purpose
…and unconsciously change their behavior*
to FIT that interpretation*

Example:

During doming trials, we remark how subject’s numbers were the “highest we’ve seen”
- This makes them think we WANT to see higher numbers
They then strive to get the highest numbers possible

(In reality, we want NATURAL doming strengths)

Answer 67

A

Information Bias

=Wrong or inexact recording of variables or data

With CONTINUOUS Variables (such as blood pressure):
- this is referred to as “Measurement Error”
With CATEGORICAL Variables (such as tumor stage):
- this is known as “Misclassification”

Example:

Continuous (measurements)
- recording them wrong
Categorical (shoe size on form)
- you put down the wrong shoe size for them

Answer 68

A

Confounding Variables (a.k.a. confounding factor, confounder)

An extraneous variable that INFLUENCES the variables being studied
- ….but is NOT part of the _expected_ correlation or causal pathway being investigated

EXAMPLE:

Suppose the relationship between A and B is being investigated
- A is hypothesized to increase B
  - Experimental results support this hypothesis
It is later discovered that a third variable (i.e., extraneous variable) influences both A and B,
- Decreasing A, and
- Increasing B
In fact, it was C that created the observed result in B that was originally attributed to A

Variable C is a confounding variable

Placebo Effect:

One example of a confounding variable
The placebo effect occurs when participants given a placebo (i.e., sham treatment) during a study experience REAL or PERCEIVED health benefits–
- due to their belief that they ARE being treated

Answer 69

A

Detection Bias

Systematic differences between groups…
…caused by inconsistency in*
the method of detection or diagnosis*

EXAMPLE:

A study reports that inner city children suffer from ADHD at twice the rate of suburban children

It is later discovered that systematic differences existed between:

diagnostic tools, and
training available
- …at inner city hospitals included in the study
- …vs. suburban hospitals included in the study
Basically, they’re detecting ADHD rates inconsistently, because suburban hospitals are able to more accurately diagnose those who REALLY have ADHD
- Inner city hospitals are quicker to just “slap a label” on ‘em

Answer 70

A

Performance Bias

Systematic differences between groups…
in terms of the*

ACTUAL CARE OR TREATMENT PROVIDED

EXAMPLE:

A physician unconsciously pays closer attention to and conducts more followup with patients the doctor knows to be enrolled in a heart study

This results in differences in care for those individuals not accounted for in the study

Answer 71

A

Experimenter Bias (a.k.a., Researcher Bias)

ERRORS introduced into a study

due to the expectations of the investigator

2 Types:
1. Confirmation Bias
2. Reporting Bias

Experimenter Bias also can include unconscious communication of expected results to the participants

…thereby influencing their behavior

Answer 72

A

Confirmation Bias:

The tendency to favor information that confirms one’s hypothesis or preconceived notions
- and to dismiss information that discredits them

(This sort of thing also happens psychologically)

Answer 73

A

Reporting Bias:

Systematic differences resulting from some findings being reported and other findings NOT being reported
Investigators may withhold or ignore data that does not support their hypothesis (if conscious and intentional this would be a clear violation of ethics)

Statistically-significant results are usually far more likely to be reported than are statistically insignificant results

…although BOTH are important to

an unbiased determination

Answer 74

A

Accuracy

is a measure of the degree to which a value represents the true or correct value

Precision

is a measure of the degree to which repeatedly measured values show the same or reproducible values
The greater the range or scatter of measurements, the less precision

Answer 75

A

RELIABILITY

Results are consistent and repeatable

VALIDITY

The test or experiment measures what it purports to measure
- …and uses methods that meet scientific standards

Failure to adhere to the standards of the scientific method or other accepted experimental best practices results in LOW internal validity

Answer 76

A

“Test-Retest” reliability

is a measure of the degree of consistency between one administration of a test and a subsequent administration of that same test (i.e. the “retest”)

“Inter-Rater” reliability

is a measure of consistency between multiple raters or evaluators

that are assigning the same values or making

the same observations

In both cases, a high value of reliability is around 1.0 and shows good internal validity

Answer 77

A

If the volume goes down by 80%, it has lost 4/5 of its value—
- which is the same as being multiplied by 1/5
- or going down by a factor of 5

Answer 78

A

125%

Same as multiplying it by 5/4

Answer 79

A

Correlation coefficients relate to linear regression analysis
A large number of trials
- involving changes in the independent variable
are graphed against the dependent variable

resulting in a SCATTER PLOT

A “Least Squares” or “Best Fit” line is drawn
- that best approximates the trend of the data points

_The correlation coefficient, r² is a measure of how tightly the DATA fit to THIS line!_

The CLOSER the data are, as a whole, to the trend line:

the HIGHER the r² value

Answer 80

A

Correlation Coefficients vary from 0 to 1

An r² value of 1.0 would be a PERFECT correlation!
The correlation coefficient is said to explain the amount of variance in y ACCOUNTED FOR by x*

Answer 81

A

Hill’s Criteria is a SET OF GUIDELINES used to evaluate whether or not a CAUSAL RELATIONSHIP exists

Temporality
Consistency
Dose-Reponse Relationship
Coherence
Plausibility
Testable by Experiment
Specificity
Strength
Analogy

Answer 82

A

Temporality:

In time, the exposure or treatment

MUST PRECEDE THE OUTCOME

If A causes B, A must occur in time prior to B

This is often considered the most important Hill Criteria

If the outcome is found to occur before the exposure in even a few cases, the potential of causality is generally REJECTED

Answer 83

A

Strength

The MAGNITUDE of the CORRELATION or association
- including statistical measures of significance

A larger correlation, larger r² value, or a smaller p value would all support causation

Answer 84

A

Consistency:

The correlation or association:

continues across MULTIPLE trials, across time, or when the study is REPLICATED by others*
In other words, the relationship is REPRODUCIBLE*

Answer 85

A

Specificity:

One of the weakest Hill Criteria

High specificity means the potential cause results in only ONE specific effect
If present, it can provide additional support for causation–
- but the lack of specificity is common in MANY established cause-effect relationships

Answer 86

A

Plausibility:

The association fits LOGICALLY within our current understanding of how a process works

The association has a logical theoretical basis

Answer 87

A

Dose-Response Relationship:

The observed response is proportional to:

the dosage or degree of the exposure or treatment

This is considered STRONG evidence of causation*
…but is NOT necessary*

Answer 88

A

Testable by Experiment:

The ASSOCIATION can be:

REPRODUCED VIA EXPERIMENT

Answer 89

A

Coherence:

The ASSOCIATION is COMPATIBLE with:

existing or previously-established science

Answer 90

A

SIMILAR associations are shown

or known to exist that are:

analogous to the

association being considered

Answer 91

A

Internal Validity

The extent to which you are able to say that:

No OTHER variables (except the one you’re studying) caused the result

…which is a function of the scientific RIGOR of the study

Answer 92

A

Necessary:

A condition that MUST be satisfied

in order for an event to occur

Sufficient:

A condition that, if satisfied,

GUARANTEES that an event WILL occur!

Answer 93

A

External Validity = GENERALIZABILITY!

=The degree to which the findings can be

extrapolated to the general population

This depends a lot on:

the SUBJECTS being tested– are the representative of the general population?

Example:

Sarah is a psychologist who teaches and does research at an expensive, private college.She’s interested in studying whether offering specific praise after a task will boost people’s self-esteem. If her hypothesis is correct, then giving someone a specific compliment on a job well done after a task will make them feel better about themselves. And if she can show that specific praise post-task boosts self-esteem, then managers at companies everywhere will be able to boost their employees’ self-esteem by offering them specific praise.*
But here’s a problem: the volunteers that Sarah gets for her study are all college students, most of them are white, and most of them are from privileged backgrounds*

Sarah worries that her results might not be applicable to people who are NOT in their late teens or early 20s, white, and rich

Answer 94

A

Information about:

The study itself
Who is in the…
- Control groups
- Treatment groups
other potentially biasing details

are concealed from:

the person DOING the assessment

Answer 95

A

Information about:

The study itself
Who is in the…
- Control groups
- Treatment groups
other potentially biasing details

are concealed from BOTH:

The SUBJECT
The person DOING the assessment (researcher)

*

Answer 96

A

Type I Error: REJECTED H0** but **SHOULDN’T HAVE

CLAIMED difference between groups

…when NONE existed

Type II ErrorSHOULD** **HAVE** rejected H0 but **DIDN’T

Did NOT claim a difference between groups

…when one DID exist

Answer 97

A

The Null Hypothesis:

H₀ is always the LACK OF A RELATIONSHIP

OR GROUP DIFFERENCE

In testing for GROUP DIFFERENCES:

H_{<strong>0</strong>}= there are NO statistically significant differences between groups

When testing for CORRELATION or CAUSATION:

H₀= there is NO RELATIONSHIP

Answer 98

A

The Alternative Hypothesis:

The PRESENCE OF A RELATIONSHIP OR GROUP DIFFERENCE

The OPPOSITE of the H₀!

In testing for group differences:

Alt. Hypothesis=there IS a difference between groups

When testing for correlation or causation:

Alt. Hypothesis= there IS a relationship.

Answer 99

A

Sample =

that portion of a population included in the data
- [e.g., U.S. veterans called in the phone survey]

SMALLER than the POPULATION

which is ALL the members in the group/category being sampled

[e.g., ALL U.S. veterans]

Answer 100

A

A statistic is a measure or data point*
(such as mean, median, etc.)*
that is calculated for the sample*

[e.g., average income among U.S. veterans in a sample]

Answer 101

A

Parameter =

a measure (such as mean, median, etc.) that is calculated for the ENTIRE population,

NOT merely the sample of the population

[e.g., average income among ALL U.S. veterans]

Answer 102

A

MEAN=

the average value

MEDIAN =

the middle of the data

MODE=

the most frequently occurring data point

RANGE=

the minimum data point ⇒maximum data point

Answer 103

A

STANDARD DEVIATION (SD) =

how tightly associated the data are TO THE MEAN

A small SD indicates:

a narrow set of data for which most values are close to the mean

A large SD indicates:

a greater spread, or wider distribution,

of the data around the mean

Answer 104

A

Normal Distribution=

Hypothetical perfect BELL-SHAPED curve f_or which the following is true:_

1 SD = 68% of the population
2 SD = 95% of the population
3 SD = 99% of the population

Answer 105

A

Assumption = Outcomes are:

INDEPENDENT
- Do NOT influence one another
MUTUALLY EXCLUSIVE
- They CANNOT occur together

Answer 106

A

AND vs. OR

AND =

MULTIPLY the probabilities of individual events to get the overall probability of BOTH events occurring

OR =

ADD the probabilities of each individual event together to get the overall probability of EITHER event occurring

Answer 107

A

t-Test or z-Test ⇒p value

The “test statistic” (either a t-value or a z-value) is calculated

This result is COMPARED to:
- a TABLE of t-values or z-values

The table gives us:

the SIGNIFICANCE LEVEL, “α,” associated with that test statistic

Answer 108

A

z-test

For a z-test, n>30
- This will mean it has a NORMAL (BELL-SHAPED) DISTRIBUTION
We’d use a t-test when our sample size is SMALL
- This will mean our graph will NOT be normally distributed (only approximately)

Answer 109

A

Significance Level (α)

α = 0.05, 0.01, 0.001*
p < 0.05 means we can be 95% confident that the results are actual/real
…RATHER than the result of random chance*
p < 0.01 means we can be 99% confident, and so forth

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