StatisticsBiomedical Sciences.txt
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What is statistics?
A field of study that involves methods for describing and analyzing data. It reduces uncertainty and provides for better decision making.

What is a population
Universe of cases or subjects of interest to the analyst. People, thins or concepts

What is a sample
An observable subset of the population. It needs to mirror the population.

What are some types of samples?
Random and Non Random

What is a random sample
All units have an equal chance of being included in the sample.

What are 3 ways to obtain a random sample?
 1. Using a table of random numbers
 2. Computer generated random samples
 3. Software selected random sample

Describe a simple random sample.
 Assign all elements a number, in a class of 25  assign 1  25
 Determine the sample size example: 5
 Use a table to assign random numbers to provide 5 random numbers between 1 and 25

Describe systematic sample
 Produce names of population
 Determine sample size (5)
 Divide the total (25) by the sample size (5) = 5
 Take every 5th name on the list for inclusion in the sample
 If the 5th person refuses, the analyst must begin the count to 5 again.

Describe a stratified sample
Divide the number of STRATA (groups) that share similar characteristics. Draw random samples from each Stratum.

Cluster Sampling is?
Sampling based on selecting clusters from a population and then sampling from those clusters. Examples: geography  rural, suburbs, city

Describe the differences between stratified and cluster sampling
Cluster samples only include a subset of the clusters. Stratified samples include all of the strata. Stratified samples allow for more precision.

Name some non random sampling types
 1. Convience samples  surveying the first 10 people in a parking lot
 2. Volunteers American Idol
 3. Judgemental sample a sample based on expert judgment
 4. Quota sample  convience sample designed to provide a certain distribution

Define sampling error
The difference between the sample and the larger population that is due to pure random chance .

What is true of sample error.
As sample size increases sampling error decreases .

Define bias
The differences between a sample and the population that are not do to pure random chance.

Describe a fact about sampling bias.
Unlike sampling error, sampling bias will not decrease as your sampling number increases .

Describe some sources of selection bias
 A group that is under represented in your samples.
 A group that fails to respond to your survey non response bias
 A group that self select so as the sample, American Idol.

Define measurement error
Inaccuracy or miscalculation of the observation , caused by unclear questions, leading questions, questions containing social desirability componant.

Define Validity
Does the instrument measure what it intended to measure.

Define Reliability
Does the instrument provide constant results over repeated measurements.

Name and describe 4 dimensions to validity
 1. Face  does the anayst have confidence in the measuring instrument
 2. Content concerned with the sample population representatives
 3. Correlative  the results have a high correlation to other established measures of validity
 4. Predictive the resilts should be able to successfully predict outcomes gre = success in a graduate program

Define external validity
Results that can be readily generalized to the larger population are said to have external validity.

Define internal validity
Did I measure what I claimed to measure by eliminating all confounding variables

List and describe 8 threats to internal validity
 1. History  external events that produce an effect that can be confused with the outcome. school program success vs economic boom happening at same time
 2. Maturation  internal factors that can be confused with outcome  treated allergies that resolve over time, due to tx or due to growth of child
 3. Testing measuring a person that can produce the effect confusing the outcome Stalins arrival improves productivity
 4. Instrumentation  changes in the measurement tool
 5. Statistical regression to the mean  selection of a group due to their deviance from the mean  odds are that next measurement that group will regressed to
 mean.
 6. Selection bias
 7. Experimental mortality subjects dropping out of study will change the composition of the sample.
 8. SelectionMaturation Interaction any bias in selection will interact with maturation to produce a greater effect than maturation alone

Name 3 research design techniques
 1. Preexperimental  policy is changed and later a decision is made to evaluate the policy
 2. Quasi Experimental  uses a comparison group. Ex: impact of affirmative action on female employment in shipyards.
 3. Experimental includes randomization componant. Participants randomly selected and randomly assigned to experimental or control group.

Describe an example of the paradox of internal and external validity
Real world clinical trials often may have a drug that is valid in a controlled setting (high internal value) but not effective in the real world where patients don't follow direction (low external validity)

List 4 levels of measurement
 1. Nominal  catagorizing information. Hair Color: 1= blond 2= brunette 3= other
 2. Ordinal  ranked in order of some rype of continuum. 1= strongly agree 2= agree 3= neutral 4= disagree 5= strongly diagree
 3. Interval  regular numbers where distance between the numbers is the same and all numbers anchored by an arbitrary zero  IQ, Temp, Test scores
 4. Ratio Scale distance between points is equal and anchored by a non arbitrary zero. Hourly wage, height, weight, age, miles driven in a day

Give some examples of Nominal data
 Gender
 Ethnicity
 Marital status

Give some examples of Ordinal Data
 Movie ratings
 Scio economic status
 Rating of meat in the store
 Rank order of anything

Name some examples of Interval Data
 Degrees F OR C
 Most personality measures
 Intelligence scores

List some examples of Ratio Data
 Annual income in dollars
 Distance as measured in miles, inches, centimeters etc..

What arithmetical operation is used for Nominal Data
Counting

What arithmetical operations can be used for Ordinal Data?
Gretaer than or less than

What arithmetical operation is permitted with Interval Data?
Addition and subtraction of the scale values

What arithmetical operation is permitted with Ratio Data?
Multiplication and division of scale values

Name the measures of central tendency begining with the most commonly used.
 1. Mean
 2. Mode
 3. Median
 4. Trimmed Mean

Define Mode
A measurement of central tendoncy that is equal to the score that occurs most often in the distribution.

Define Median
The score that divides the distribution in half. =(n + 1) / 2 will identify the positon of the median

Define the Mean
The arithmetic average of scores. Sum the scores and divide by the number of scores.

Which measures of central tendoncy are not useful in statistical decsion making but may be helpful interms of describing them
Mode and Median